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This document discusses criteria for effectively organizing and presenting numeric data in tables, charts, and prose. It explains that the order of variables should coordinate with any accompanying text description and considers principles for ordering variables, including using the order from the original data collection, alphabetical order, empirical patterns in the data, and theoretical groupings. The document also provides examples showing different ways of ordering variables for various purposes like reporting survey results or expenditures by category.

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Katagorisel veri analizi

This document provides an overview of categorical data analysis techniques. It discusses chi-square tests for independence and their limitations in describing association strength. Better measures include comparing proportions, calculating odds ratios, and examining concordant/discordant pairs. Larger sample sizes can make weak associations appear statistically significant with chi-square tests, so other measures are preferable. The document also covers logistic regression and residual analysis for categorical data.

Lesson 2 Statistics Benefits, Risks, and MeasurementsAssignmen.docx

Lesson 2: Statistics: Benefits, Risks, and Measurements
Assignments
· See your Course Syllabus for the reading assignments.
· Work through the Lesson 2 online notes that follow.
· Complete the Practice Questions and Lesson 2 Assignment.
Learning Objectives
Chapters 1 and 3
After successfully completing this lesson, you should be able to:
· Identify the three conditions needed to conduct a proper study.
· Apply the seven pitfalls that can be encountered when asking questions in a survey.
· Distinguish between measurement variables and categorical variables.
· Distinguish between continuous variables and discrete variables for those that are measurement variables.
· Distinguish between validity, reliability, and bias.
Terms to Know
From Chapter 1
· statistics
· population
· sample
· observational study
· experiment
· selection bias
· nonresponse bias
From Chapter 3
· data (variable)
· categorical variables
· measurement variables
· measurement (discrete) variables
· measurement (continuous) variables
· validity
· reliability
· bias
2.1 What is Statistics?
Section 2.1. Chapter 1
Overview
What is statistics? If you think statistics is just another math course with many formulas and lifeless numbers, you are not alone. However, this is a myth that hopefully will be debunked as you work through this course. Statistics is about data. More precisely, statistics is a collection of procedures and principles for gaining and processing information from collected data. Knowing these principles and procedures will help you make intelligent decisions in everyday life when faced with uncertainty. The following examples are meant to illuminate the definition of statistics.
Example 2.1. Angry Women
Who are those angry women? (Streitfield, D., 1988 and Wallis, 1987.) In 1987, Shere Hite published a best-selling book called Women and Love: A Cultural Revolution in Progress. This 7-year research project produced a controversial 922-page publication that summarized the results from a survey that was designed to examine how American women feel about their relationships with men. Hite mailed out 100,000 fifteen-page questionnaires to women who were members of a wide variety of organizations across the U.S. These organizations included church, political, volunteer, senior citizen, and counseling groups, among many others. Questionnaires were actually sent to the leader of each organization. The leader was asked to distribute questionnaires to all members. Each questionnaire contained 127 open-ended questions with many parts and follow-ups. Part of Hite’s directions read as follows: “Feel free to skip around and answer only those questions you choose.” Approximately 4500 questionnaires were returned. Below are a few statements from this 1987 publication.
· 84% of women are not emotionally satisfied with their relationships
· 95% of women reported emotional and psychological harassment from their partners
· 70% of women married 5 years or more are having extramarital ...

Statistics What you Need to KnowIntroductionOften, when peop.docx

Statistics: What you Need to Know
Introduction
Often, when people begin a statistics course, they worry about doing advanced mathematics or their math phobias kick in. Understanding that statistics as addressed in this course is not a math course at all is important. The only math you will do is addition, subtraction, multiplication, and division. In these days of computer capability, you generally don't even have to do that much, since Excel is set up to do basic statistics for you. The key elements for the student in this course is to understand the various types of statistics, what their requirements are, what they do, and how you can use and interpret the results. Referring back to the basic components of a valid research study, which statistic a researcher uses depends on several things:
The research question itself
The sample size
The type of data you have collected
The type of statistic called for by the design
All quantitative studies require a data set. Qualitative studies may use a data set or may use observations with no numerical data at all. For the purposes of the next modules, our focus will be on quantitative studies.
Types of Statistics
There are several types of statistics available to the researcher. Descriptive statistics provide a basic description of the data set. This includes the measures of central tendency: means, medians, and modes, and the measures of dispersion, including variances and standard deviations. Descriptive statistics also include the sample size, or "N", and the frequency with which each data point occurs in the data set.
Inferential statistics allow the researcher to make predictions, estimations, and generalizations about the data set, the sample, and the population from which the sample was drawn. They allow you to draw inferences, generalizations, and possibilities regarding the relationship between the independent variable and the dependent variable to indicate how those inferences answer the research question. Researchers can make predictions and estimations about how the results will fit the overall population. Statistics can also be described in terms of the types of data they can analyze. Non-parametric statistics can be used with nominal or ordinal data, while parametric statistics can be used with interval and ratio data types.
Types of Data
There are four types of data that a researcher may collect.
Nominal Data Sets
The Nominal data set includes simple classifications of data into categories which are all of equal weight and value. Examples of categories that are equal to each other include gender (male, female), state of birth (Arizona, Wyoming, etc.), membership in a group (yes, no). Each of these categories is equivalent to the other, without value judgments.
Ordinal Data Sets
Ordinal data sets also have data classified into categories, but these categories have some form or order or ranking attached, often of some sort of value / val.

Research

The document discusses different types of research methods and designs, including experimental, quasi-experimental, non-experimental, qualitative, and quantitative approaches. It provides examples of true experimental designs, quasi-experimental designs, and non-experimental designs. It also outlines the key differences between qualitative and quantitative research, such as qualitative research being inductive while quantitative research is deductive. Finally, it discusses developing research questions and hypotheses for different types of studies.

Module 3 - CasePERFORM THE RESEARCHCase AssignmentThe Situatio.docx

Module 3 - Case
PERFORM THE RESEARCH
Case Assignment
The Situation
It is argued that perceptions of service quality vary across cultural groups, as defined by each culture's position on Hofstede's dimensions. The relationship is explicitly mapped between service quality perceptions and cultural dimension positions and the implications drawn for international service market segmentation. The hypotheses constituting their theoretical analysis are also tested. It is shown that the importance of SERVQUAL dimensions is correlated with Hofstede's cultural dimensions. Correlation coefficients are also used to compute a Cultural Service Quality Index that could be used to segment international service markets and allocate resources across segments.
Case Resource
Furrer, Olivier; Shaw-Ching, Ben; & Sudharshan (2000). The Relationships between Culture and Service Quality Perceptions: Basis for Cross-Cultural Market Segmentation and Resource Allocation.
Journal of Service Research,
2:4:(May):355-72. Available November 30, 2012 via EBSCO
Upload your 4-6 page paper by the module deadline.
Assignment Expectations
In preparing CASE3, that is, in preparing your analysis of Furrer, Shaw-Ching, & Sudharshan (2000), ensure that you demonstrate your learning of the marketing research concepts and frameworks for analysis outlined as follows:
Evaluate a Questionnaire
Describe the tradeoffs that need to be made between research design, cost, project implementability, and expected results
Problem
? What is the driving force or main purpose behind this article? Is the problem important (yes or no)? Why was this article written? Defend your positions on all of these issues.
Central hypothesis
? What is the main proposition that the author is trying to express/explore? Is your (the central) hypothesis best classified as descriptive, explanatory, or predictive/causal? Does the main hypothesis call for a measure of association or a measure of difference between two variables? What is the theoretical basis of your (the central) hypothesis? Does this hypothesis logically flow from and relate to the theorized constructs and relationships presented as the basis for the research or was it picked out of thin air? Defend your positions on all of these issues.
Research design
? Is the study and experiment, a quasi-experiment, or a correlation? Defend your position on this issue
Construct Validity
? In your (the central) hypothesis, look for a description of how the cause (that is, the independent (or predictor variable(s)) and the effect (that is, the dependent (or criterion variable(s)) are being measured. Face Validity: Do the measures measure what they are supposed to measure? Internal reliability: Are the measures reliable? What level of measurement is applied to these variables (for example, for each, identify if they are nominal, ordinal, scalar). What is the unit of analysis (for example, is it individual, group, corporate, societal)? Does the unit of analysis match bet.

MELJUN CORTES research seminar_1__data_analysis_basics_slides_2nd_updates

This document discusses the basics of descriptive data analysis, including defining different types of variables, coding principles, and univariate data analysis. It describes continuous variables, which are always numeric, and categorical variables such as ordinal, nominal, and dichotomous. The document outlines how to code different variable types using values and labels and provides examples. It also covers cleaning data, calculating basic statistics, and examining the distribution and frequencies of variables to check data quality in univariate analysis.

QUESTION 11. The collection of all elements of interest in a par.docx

QUESTION 1
1. The collection of all elements of interest in a particular study is
the population
the sampling
statistical inference
Data and Statistics
5 points
QUESTION 2
1. A portion of the population selected to represent the population is called
statistical inference
Data and Statistics
a census
a sample
5 points
QUESTION 3
1. The process of analyzing sample data in order to draw conclusions about the characteristics of a population is called
Data and Statistics
statistical inference
data analysis
data summarization
5 points
QUESTION 4
1. Categorical data
indicate either how much or how many
annot be numeric
are labels used to identify attributes of elements
must be nonnumeric
5 points
QUESTION 5
1. Quantitative data
are always nonnumeric
may be either numeric or nonnumeric
are always numeric
None of these alternatives is correct.
5 points
QUESTION 6
1. In a questionnaire, respondents are asked to mark their gender as male or female. Gender is an example of a
categorical variable
quantitative variable
categorical or quantitative variable, depending on how the respondents answered the question
None of these alternatives is correct.
5 points
QUESTION 7
1. The average age in a sample of 190 students at City College is 22. As a result of this sample, it can be concluded that the average age of all the students at City College
must be more than 22, since the population is always larger than the sample
must be less than 22, since the sample is only a part of the population
could not be 22
could be larger, smaller, or equal to 22
5 points
QUESTION 8
1. A statistics professor asked students in a class their ages. On the basis of this information, the professor states that the average age of all the students in the university is 24 years. This is an example of
a census
Data and Statistics
an experiment
statistical inference
5 points
QUESTION 9
1. A graphical presentation of the relationship between two variables is
an ogive
a histogram
either an ogive or a histogram, depending on the type of data
a scatter diagram
5 points
QUESTION 10
1. The can be used to show the rank order and shape of a data set simultaneously.
Ogive
pie chart
stem-and-leaf display
bar chart
5 points
QUESTION 11
1. Which of the following is a graphical summary of a set of data in which each data value is represented by a dot above the axis?
histogram
box plot
dot plot
crosstabulation
10 points
QUESTION 12
1. Categorical data can be graphically represented by using a(n)
histogram
frequency polygon
ogive
bar chart
10 points
QUESTION 13
1. A tabular summary of a set of data showing the fraction of the total number of items in several classes is a
frequency distribution
relative frequency distribution
frequency
cumulative frequency distribution
10 points
QUESTION 14
1. Fifteen percent of the students in a school of Business Administration a ...

Dataset Codebook BUS7105, Week 8 Name Source Represe

This document provides a codebook describing variables in a dataset collected through an online survey. It defines 12 variables including subject identification number, gender, age, education level, personality traits, job satisfaction, engagement, trust in leader, motivation, and intent to quit. For each variable, it identifies the data source and type (e.g. categorical, continuous), measurement scale, and response values and their meanings. It also discusses measurement levels and provides references on using Likert scales in statistical analysis.

Katagorisel veri analizi

This document provides an overview of categorical data analysis techniques. It discusses chi-square tests for independence and their limitations in describing association strength. Better measures include comparing proportions, calculating odds ratios, and examining concordant/discordant pairs. Larger sample sizes can make weak associations appear statistically significant with chi-square tests, so other measures are preferable. The document also covers logistic regression and residual analysis for categorical data.

Lesson 2 Statistics Benefits, Risks, and MeasurementsAssignmen.docx

Lesson 2: Statistics: Benefits, Risks, and Measurements
Assignments
· See your Course Syllabus for the reading assignments.
· Work through the Lesson 2 online notes that follow.
· Complete the Practice Questions and Lesson 2 Assignment.
Learning Objectives
Chapters 1 and 3
After successfully completing this lesson, you should be able to:
· Identify the three conditions needed to conduct a proper study.
· Apply the seven pitfalls that can be encountered when asking questions in a survey.
· Distinguish between measurement variables and categorical variables.
· Distinguish between continuous variables and discrete variables for those that are measurement variables.
· Distinguish between validity, reliability, and bias.
Terms to Know
From Chapter 1
· statistics
· population
· sample
· observational study
· experiment
· selection bias
· nonresponse bias
From Chapter 3
· data (variable)
· categorical variables
· measurement variables
· measurement (discrete) variables
· measurement (continuous) variables
· validity
· reliability
· bias
2.1 What is Statistics?
Section 2.1. Chapter 1
Overview
What is statistics? If you think statistics is just another math course with many formulas and lifeless numbers, you are not alone. However, this is a myth that hopefully will be debunked as you work through this course. Statistics is about data. More precisely, statistics is a collection of procedures and principles for gaining and processing information from collected data. Knowing these principles and procedures will help you make intelligent decisions in everyday life when faced with uncertainty. The following examples are meant to illuminate the definition of statistics.
Example 2.1. Angry Women
Who are those angry women? (Streitfield, D., 1988 and Wallis, 1987.) In 1987, Shere Hite published a best-selling book called Women and Love: A Cultural Revolution in Progress. This 7-year research project produced a controversial 922-page publication that summarized the results from a survey that was designed to examine how American women feel about their relationships with men. Hite mailed out 100,000 fifteen-page questionnaires to women who were members of a wide variety of organizations across the U.S. These organizations included church, political, volunteer, senior citizen, and counseling groups, among many others. Questionnaires were actually sent to the leader of each organization. The leader was asked to distribute questionnaires to all members. Each questionnaire contained 127 open-ended questions with many parts and follow-ups. Part of Hite’s directions read as follows: “Feel free to skip around and answer only those questions you choose.” Approximately 4500 questionnaires were returned. Below are a few statements from this 1987 publication.
· 84% of women are not emotionally satisfied with their relationships
· 95% of women reported emotional and psychological harassment from their partners
· 70% of women married 5 years or more are having extramarital ...

Statistics What you Need to KnowIntroductionOften, when peop.docx

Statistics: What you Need to Know
Introduction
Often, when people begin a statistics course, they worry about doing advanced mathematics or their math phobias kick in. Understanding that statistics as addressed in this course is not a math course at all is important. The only math you will do is addition, subtraction, multiplication, and division. In these days of computer capability, you generally don't even have to do that much, since Excel is set up to do basic statistics for you. The key elements for the student in this course is to understand the various types of statistics, what their requirements are, what they do, and how you can use and interpret the results. Referring back to the basic components of a valid research study, which statistic a researcher uses depends on several things:
The research question itself
The sample size
The type of data you have collected
The type of statistic called for by the design
All quantitative studies require a data set. Qualitative studies may use a data set or may use observations with no numerical data at all. For the purposes of the next modules, our focus will be on quantitative studies.
Types of Statistics
There are several types of statistics available to the researcher. Descriptive statistics provide a basic description of the data set. This includes the measures of central tendency: means, medians, and modes, and the measures of dispersion, including variances and standard deviations. Descriptive statistics also include the sample size, or "N", and the frequency with which each data point occurs in the data set.
Inferential statistics allow the researcher to make predictions, estimations, and generalizations about the data set, the sample, and the population from which the sample was drawn. They allow you to draw inferences, generalizations, and possibilities regarding the relationship between the independent variable and the dependent variable to indicate how those inferences answer the research question. Researchers can make predictions and estimations about how the results will fit the overall population. Statistics can also be described in terms of the types of data they can analyze. Non-parametric statistics can be used with nominal or ordinal data, while parametric statistics can be used with interval and ratio data types.
Types of Data
There are four types of data that a researcher may collect.
Nominal Data Sets
The Nominal data set includes simple classifications of data into categories which are all of equal weight and value. Examples of categories that are equal to each other include gender (male, female), state of birth (Arizona, Wyoming, etc.), membership in a group (yes, no). Each of these categories is equivalent to the other, without value judgments.
Ordinal Data Sets
Ordinal data sets also have data classified into categories, but these categories have some form or order or ranking attached, often of some sort of value / val.

Research

The document discusses different types of research methods and designs, including experimental, quasi-experimental, non-experimental, qualitative, and quantitative approaches. It provides examples of true experimental designs, quasi-experimental designs, and non-experimental designs. It also outlines the key differences between qualitative and quantitative research, such as qualitative research being inductive while quantitative research is deductive. Finally, it discusses developing research questions and hypotheses for different types of studies.

Module 3 - CasePERFORM THE RESEARCHCase AssignmentThe Situatio.docx

Module 3 - Case
PERFORM THE RESEARCH
Case Assignment
The Situation
It is argued that perceptions of service quality vary across cultural groups, as defined by each culture's position on Hofstede's dimensions. The relationship is explicitly mapped between service quality perceptions and cultural dimension positions and the implications drawn for international service market segmentation. The hypotheses constituting their theoretical analysis are also tested. It is shown that the importance of SERVQUAL dimensions is correlated with Hofstede's cultural dimensions. Correlation coefficients are also used to compute a Cultural Service Quality Index that could be used to segment international service markets and allocate resources across segments.
Case Resource
Furrer, Olivier; Shaw-Ching, Ben; & Sudharshan (2000). The Relationships between Culture and Service Quality Perceptions: Basis for Cross-Cultural Market Segmentation and Resource Allocation.
Journal of Service Research,
2:4:(May):355-72. Available November 30, 2012 via EBSCO
Upload your 4-6 page paper by the module deadline.
Assignment Expectations
In preparing CASE3, that is, in preparing your analysis of Furrer, Shaw-Ching, & Sudharshan (2000), ensure that you demonstrate your learning of the marketing research concepts and frameworks for analysis outlined as follows:
Evaluate a Questionnaire
Describe the tradeoffs that need to be made between research design, cost, project implementability, and expected results
Problem
? What is the driving force or main purpose behind this article? Is the problem important (yes or no)? Why was this article written? Defend your positions on all of these issues.
Central hypothesis
? What is the main proposition that the author is trying to express/explore? Is your (the central) hypothesis best classified as descriptive, explanatory, or predictive/causal? Does the main hypothesis call for a measure of association or a measure of difference between two variables? What is the theoretical basis of your (the central) hypothesis? Does this hypothesis logically flow from and relate to the theorized constructs and relationships presented as the basis for the research or was it picked out of thin air? Defend your positions on all of these issues.
Research design
? Is the study and experiment, a quasi-experiment, or a correlation? Defend your position on this issue
Construct Validity
? In your (the central) hypothesis, look for a description of how the cause (that is, the independent (or predictor variable(s)) and the effect (that is, the dependent (or criterion variable(s)) are being measured. Face Validity: Do the measures measure what they are supposed to measure? Internal reliability: Are the measures reliable? What level of measurement is applied to these variables (for example, for each, identify if they are nominal, ordinal, scalar). What is the unit of analysis (for example, is it individual, group, corporate, societal)? Does the unit of analysis match bet.

MELJUN CORTES research seminar_1__data_analysis_basics_slides_2nd_updates

This document discusses the basics of descriptive data analysis, including defining different types of variables, coding principles, and univariate data analysis. It describes continuous variables, which are always numeric, and categorical variables such as ordinal, nominal, and dichotomous. The document outlines how to code different variable types using values and labels and provides examples. It also covers cleaning data, calculating basic statistics, and examining the distribution and frequencies of variables to check data quality in univariate analysis.

QUESTION 11. The collection of all elements of interest in a par.docx

QUESTION 1
1. The collection of all elements of interest in a particular study is
the population
the sampling
statistical inference
Data and Statistics
5 points
QUESTION 2
1. A portion of the population selected to represent the population is called
statistical inference
Data and Statistics
a census
a sample
5 points
QUESTION 3
1. The process of analyzing sample data in order to draw conclusions about the characteristics of a population is called
Data and Statistics
statistical inference
data analysis
data summarization
5 points
QUESTION 4
1. Categorical data
indicate either how much or how many
annot be numeric
are labels used to identify attributes of elements
must be nonnumeric
5 points
QUESTION 5
1. Quantitative data
are always nonnumeric
may be either numeric or nonnumeric
are always numeric
None of these alternatives is correct.
5 points
QUESTION 6
1. In a questionnaire, respondents are asked to mark their gender as male or female. Gender is an example of a
categorical variable
quantitative variable
categorical or quantitative variable, depending on how the respondents answered the question
None of these alternatives is correct.
5 points
QUESTION 7
1. The average age in a sample of 190 students at City College is 22. As a result of this sample, it can be concluded that the average age of all the students at City College
must be more than 22, since the population is always larger than the sample
must be less than 22, since the sample is only a part of the population
could not be 22
could be larger, smaller, or equal to 22
5 points
QUESTION 8
1. A statistics professor asked students in a class their ages. On the basis of this information, the professor states that the average age of all the students in the university is 24 years. This is an example of
a census
Data and Statistics
an experiment
statistical inference
5 points
QUESTION 9
1. A graphical presentation of the relationship between two variables is
an ogive
a histogram
either an ogive or a histogram, depending on the type of data
a scatter diagram
5 points
QUESTION 10
1. The can be used to show the rank order and shape of a data set simultaneously.
Ogive
pie chart
stem-and-leaf display
bar chart
5 points
QUESTION 11
1. Which of the following is a graphical summary of a set of data in which each data value is represented by a dot above the axis?
histogram
box plot
dot plot
crosstabulation
10 points
QUESTION 12
1. Categorical data can be graphically represented by using a(n)
histogram
frequency polygon
ogive
bar chart
10 points
QUESTION 13
1. A tabular summary of a set of data showing the fraction of the total number of items in several classes is a
frequency distribution
relative frequency distribution
frequency
cumulative frequency distribution
10 points
QUESTION 14
1. Fifteen percent of the students in a school of Business Administration a ...

Dataset Codebook BUS7105, Week 8 Name Source Represe

This document provides a codebook describing variables in a dataset collected through an online survey. It defines 12 variables including subject identification number, gender, age, education level, personality traits, job satisfaction, engagement, trust in leader, motivation, and intent to quit. For each variable, it identifies the data source and type (e.g. categorical, continuous), measurement scale, and response values and their meanings. It also discusses measurement levels and provides references on using Likert scales in statistical analysis.

Correlation and Regression Study.docx

1. The document discusses a research assignment requiring students to identify a research question from Week 1 that is suitable for a correlational study using correlation or regression analysis.
2. One example research question is "How does employees' motivation affect organizational productivity?", with motivation factors and productivity as variables that could be measured on an ordinal scale.
3. The document provides 10 total example research questions, describes their variables, and discusses appropriate measurement scales for analysis. It also lists required and recommended resources on research methods, correlation, and regression.

Community Teaching Plan Teaching Experience Paper 1Unsatisf.docx

Community Teaching Plan: Teaching Experience Paper
1
Unsatisfactory
0.00%
2
Less than Satisfactory
75.00%
3
Satisfactory
83.00%
4
Good
94.00%
5
Excellent
100.00%
80.0 %Content
30.0 %Comprehensive Summary of Teaching Plan With Epidemiological Rationale for Topic
Summary of community teaching plan is not identified or missing.
Summary of community teaching plan is incomplete.
Summary of community teaching plan is offered but some elements are vague.
Focus of community teaching is clear with a detailed summary of each component. Rationale is not provided.
Focus of community teaching is clear, consistent with Functional Health Patterns (FHP) assessment findings and supported by explanation of epidemiological rationale.
50.0 %Evaluation of Teaching Experience With Discussion of Community Response to Teaching Provided. Areas of Strength and Areas of Improvement Described
Evaluation of teaching experience is omitted or incomplete.
Evaluation of teaching experience is unclear and/or discussion of community response to teaching is missing.
Evaluation of teaching experience is provided with a brief discussion of community response to teaching.
A detailed evaluation of teaching experience with discussion of community response to teaching and areas of strength/improvement is provided.
Comprehensive evaluation of teaching experience with discussion of community response provided along with a detailed description of barriers and strategies to overcome barriers is provided.
15.0 %Organization and Effectiveness
5.0 %Thesis Development and Purpose
Paper lacks any discernible overall purpose or organizing claim.
Thesis is insufficiently developed and/or vague; purpose is not clear.
Thesis is apparent and appropriate to purpose.
Thesis is clear and forecasts the development of the paper. It is descriptive and reflective of the arguments and appropriate to the purpose.
Thesis is comprehensive; contained within the thesis is the essence of the paper. Thesis statement makes the purpose of the paper clear.
5.0 %Paragraph Development and Transitions
Paragraphs and transitions consistently lack unity and coherence. No apparent connections between paragraphs are established. Transitions are inappropriate to purpose and scope. Organization is disjointed.
Some paragraphs and transitions may lack logical progression of ideas, unity, coherence, and/or cohesiveness. Some degree of organization is evident.
Paragraphs are generally competent, but ideas may show some inconsistency in organization and/or in their relationships to each other.
A logical progression of ideas between paragraphs is apparent. Paragraphs exhibit a unity, coherence, and cohesiveness. Topic sentences and concluding remarks are appropriate to purpose.
There is a sophisticated construction of paragraphs and transitions. Ideas progress and relate to each other. Paragraph and transition construction guide the reader. Paragraph structure is seamless.
5.0 %Mechanics of Writing (includes spelling.

Nursing Research Methods Discussion Assignment.pdf

This document discusses qualitative research methods and their use in nursing research. It argues that both qualitative and quantitative research have important roles to play in evidence-based practice and improving patient outcomes. Qualitative research aims to provide rigorous analysis and thorough understanding of complex issues. The document analyzes a chosen qualitative research article on its rigor and methods. It finds the article establishes rigor through its data collection and analysis methods, which systematically generate taxonomy, themes, and theory on the research topic.

Poe_STUDY GUIDE_term 2.docx.pptx

The document outlines the topics and lectures covered in an introductory research methods course, including defining variables, developing study designs, sampling methods, data collection tools and techniques, and addressing potential biases and ethical considerations. Key areas discussed are determining sample sizes, developing quantitative and qualitative indicators, choosing sampling strategies, designing data collection instruments, and mitigating biases during the research process.

MELJUN CORTES research seminar_1__data_analysis_basics_slides

This document discusses the basics of descriptive data analysis, including defining different types of variables, coding principles, and univariate data analysis. It describes continuous variables as always numeric and categorical variables as information sorted into categories, with ordinal variables having intrinsic order, nominal variables lacking order, and dichotomous variables having only two levels. The document outlines steps for coding variables and cleaning data, as well as techniques for univariate analysis of continuous and categorical variables to check data quality.

MELJUN CORTES research seminar_1_data_analysis_basics

This document discusses the basics of descriptive data analysis, including defining different types of variables, coding principles, and univariate data analysis. It describes continuous and categorical variables, including ordinal, nominal, and dichotomous variables. The document outlines steps for coding variables and cleaning data, as well as techniques for univariate analysis of continuous and categorical variables, including examining distributions, frequencies, and comparing observed vs expected values. The goal is to familiarize readers with fundamental concepts for organizing, coding, and performing initial exploratory analysis of data.

Graduate Students’ Perceptions of Work and Family: Gender and Program Compari...

Recent political debates have suggested that the United States is on the verge of a crisis and their position as a leader in producing talented and ambitious individuals in technical professions, such as engineering, is in jeopardy. A National Academy of Sciences 2006 report stated, “the United States can no longer afford the underperformance of our academic institutions in attracting the best and brightest minds to the science and engineering enterprise. Nor can it afford to devalue the contributions of some members of that workforce through gender inequities and discrimination” (2006).
Recent years have seen the movement of women into male-predominated programs and the movement of some programs toward gender-neutral compositions. However, a study of undergraduate college women revealed that women in male-predominated programs were more likely than those in female-predominated programs to report thinking about changing their major (Steele, James, & Bartnett, 2002) indicating that there is a problem in retaining these women recruited into male-predominated programs.
This study assessed perceptions of family supportiveness in academic program and anticipated career, anticipated career barriers, gender ideology and strategies for combining career and family among 181 graduate students from male-predominated, female-predominated, and gender-neutral programs at 11 research-extensive universities in the United States. Gender and program comparisons in perceptions of family supportiveness and anticipated career barriers were examined.
Unexpectedly, students in female-predominated programs perceived their programs and future careers to be less supportive of families than students in other programs. Women also anticipated more barriers to their chosen careers than men, with a significant gender by program interaction with women in male-predominated programs anticipating the most severe career barriers. While an egalitarian gender ideology was found to be a significant predictor of career scaling back for women it was not associated with career scaling back for men.

© 2016 Laureate Education, Inc. 1 of 3 SOCW 6301 W.docx

© 2016 Laureate Education, Inc. 1 of 3
SOCW 6301: Week 10 Assignment Guidelines
Quantitative Article Review and Critique
In approximately 7-10 pages (including title page and references), address the
following questions.
Title
After reading the entire article, do you think the title adequately describes
the study? Does the title catch your attention? Please explain.
Abstract
Does the abstract contain the recommended content (see “Abstract,”
pp. 314, in Yegidis et al.)? How difficult do you think it is to
summarize so much information in 150–250 words? Please explain.
Introduction
Why did the authors conduct this study and write this article? What was the
problem of interest or concern? Be specific. Use quotes and paraphrases
with citations. What audience might be interested in this study?
Do you feel the problem is significant enough to warrant a journal article?
Did you have a “so what” reaction? If so, why do you think it was accepted
for publication? Please justify your position.
To what extent does the literature presented in the introduction help you
understand the problem? How does the literature reviewed put the problem
in context? Be specific.
Does the researcher indicate how this research is different from and/or
similar to earlier ones reported in the literature? Summarize what this
article intends to add to the knowledge base.
Do the authors state their research questions and/or hypotheses? What
are the hypotheses or focused research questions?
Methods
What specific quantitative method is used? How does a quantitative
research design correspond with the research questions or hypotheses?
Can you determine whether the design was appropriate?
© 2016 Laureate Education, Inc. 2 of 3
To what extent can the design answer the research questions or
address the stated hypotheses? Elaborate.
What were the variables under study? If relevant, identify the main dependent
and independent variables. If not relevant, why are there no dependent and
independent variables? What instruments or observations were used in the
research? Explain why you do, or do not, think that the methods used to
collect the data are described clearly enough to allow for replication. Be
specific and please elaborate.
Explain whether or not information was provided concerning the reliability and
validity of these instruments or observations. Was this information adequate?
How does the presence or absence of information about reliability and validity
affect your confidence in the quality of the study? What have the authors
done to address or strengthen internal validity? Be specific.
Sample
How were the participants recruited or selected for the study? What sampling
strategy was used? Is the sample large enough to address the hypotheses
and research questions? Did the author(s) offer any justification for the
sample size? Are you satisfied with the in.

Strategic Management and Organizational Change 1Unsatisfacto.docx

Strategic Management and Organizational Change
1
Unsatisfactory
0.00%
2
Less than Satisfactory
65.00%
3
Satisfactory
75.00%
4
Good
85.00%
5
Excellent
100.00%
100.0 %Content
40.0 %Address Types of Health Care Organizational Structure, Including How the Type of Structure Impacts the Process and Effectiveness of Change
Does not demonstrate understanding of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Does not demonstrate critical thinking and analysis of the distinction between organizational and transformational change, and does not include examples or descriptions.
Demonstrates only minimal understanding of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Demonstrates only minimal abilities for making the distinction between organizational and transformational change, and does not include examples or descriptions.
Demonstrates knowledge of health care organizational structure and how the type of structure impacts the process and effectiveness of change, but has some slight misunderstanding of the distinction between organizational and transformational change. Provides a basic idea of critical thinking and analysis for the questions, answers, and rationale. Does not include examples or descriptions.
Demonstrates acceptable knowledge of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Develops an acceptable distinction between organizational and transformational change. Utilizes some examples of leadership models, tools, and advice.
Demonstrates thorough knowledge of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Clearly differentiates between organizational and transformational change. Introduces appropriate examples of leadership models, tools, and advice.
30.0 %Integrates Information From Outside Resources Into the Body of Paper
Does not use references, examples, or explanations.
Provides some supporting examples, but minimal explanations and no published references.
Supports main points with examples and explanations, but fails to include published references to support claims and ideas.
Supports main points with references, explanations, and examples. Analysis and description is direct, competent, and appropriate of the criteria.
Supports main points with references, examples, and full explanations of how they apply. Thoughtfully, analyzes, evaluates, and describes major points of the criteria.
7.0 %Assignment Development and Purpose
Paper lacks any discernible overall purpose or organizing claim.
Thesis and/or main claim are insufficiently developed and/or vague; purpose is not clear.
Thesis and/or main claim are apparent and appropriate to purpose.
Thesis and/or main claim are clear and forecast the development of the paper. It is descriptive and reflective.

1 Crosstabs Lesson 1 Running crosstabs to test you.docx

1
Crosstabs
Lesson 1: Running crosstabs to test your hypothesis
To access the Crosstabs in your SPSS, click the following:
Analyze Descriptive Statistics Crosstabs
Once you work your way through these selections, you should reach this dialog box:
You will want to place your dependent variable in the row variable and your independent variable in the
column variable. For this example, we will use AFFRMACT (preference for affirmative action policies) for
the dependent variable and SEX (gender of the respondent) as the independent variable.
2
Now we want to tell SPSS to compute the column percentages. To do this you will choose ‘Cells’ and
then select ‘Column’ in the “Percentages” box; then click ‘Continue’.
Now select ‘OK’ to run your crosstabs. You should get the following results:
3
Lesson 2: Examining Your Output
We just ran crosstabs to test a hypothesis with two variables, one nominal (SEX-independent variable)
and one ordinal (AFFRMACT-dependent variable). As you can see, the categories of the independent
variable are found across the top in the columns and the dependent variable information is found down
the side forming the rows. Each square is known as a cell and within each cell is the frequency (or
count) and the column percentage. You can also find the row totals and column totals, which are
sometimes referred to as marginal.
In our example we know the following is true:
7.8% of men in this sample strongly support affirmative action policies, whereas 11.4% of
women do;
We can also look at grouping at a glance and concede that 15% of men and 18.5% of women
support affirmative action policies in comparison to 84.9% of men and 81.5% of women oppose
these policies.
The bottom right cell in the table is where we can find that we had 1,904 people answer this
question as our sample.
Lesson 3: Interpreting Crosstabs
Researchers run crosstabs to determine whether there is an association between two variables. Also,
crosstabs may tell us other important things about the relationship between the two variables, including
the strength of association, and sometimes the direction of the association. FYI, the direction can only
be found when both of the variables in your table are greater than nominal.
Ask yourself the following questions after you populate your crosstabs:
1. Is there an association between the two variables?
If you answer yes to this (or maybe), then move to question 2.
2. What is the strength of association between the two variables?
If BOTH variables are ordinal than move to question 3.
3. What is the direction of association?
Is there an association?
What we are trying to determine here is whether knowing the value of one variable will help us predict
the value of another variable. In other words, if gender is associated with preference to affirmative
action policies. In orde ...

Research Critique of a Published Quantitative Research.docx

The study aimed to evaluate women's experiences of postnatal distress during the first year after childbirth. Semi-structured interviews were conducted with 17 women who had experienced psychological issues after giving birth. The interviews were analyzed using Interpretative Phenomenological Analysis. The results indicated that women experience various emotional difficulties following childbirth, associated with adjusting to their new role as mothers. The study provides insights that could help improve support for women after childbirth.

POLI_399_tutorial_4

This document discusses causal modeling and how to establish causal relationships between variables. It provides examples of different types of causal models, including an intervening variable model and a source of spuriousness model. Guidelines are given for including key elements in a causal model such as labeling variables, indicating the direction of relationships, and incorporating intervening or antecedent variables from the literature. The document also demonstrates how to construct causal models using Microsoft Word.

Assessment 1PRINTAnalysis of Position Papers for Vulnerabl.docx

The document provides instructions for an assessment requiring students to analyze position papers on a health care issue related to a vulnerable population. Students must explain their position on the issue, the role of an interprofessional team, and evaluate supporting and opposing evidence and positions. The analysis should be 4-6 pages, cite 3-5 supporting and 2-3 opposing sources, and follow APA style formatting. The target population and issue will be used for future assessments to potentially create a new policy.

Stat11t Chapter1

This document provides an overview of key concepts from Chapter 1 of the textbook "Elementary Statistics". It defines important statistical terms like population, sample, parameter, and statistic. It also distinguishes between different types of data and levels of measurement. Additionally, it discusses the importance of collecting sample data through appropriate random sampling methods. Critical thinking in statistics is emphasized, highlighting factors like the context, source, and sampling method of data when evaluating statistical claims. Different ways of collecting data through studies and experiments are also introduced.

Stat11t chapter1

The document summarizes key concepts from Chapter 1 of the textbook "Elementary Statistics" including:
- The difference between a population and a sample, and how statistics uses samples to make inferences about populations.
- The different types of data: quantitative, categorical, discrete vs. continuous data.
- The different levels of measurement for data: nominal, ordinal, interval, and ratio.
- The importance of critical thinking when analyzing data and statistics, including considering context, sources, sampling methods, and avoiding misleading graphs, samples, conclusions, or survey questions.

Exercise Identity Development in Adolescence Psychology of .docx

Exercise: Identity Development in Adolescence
Psychology of Adolescence (PSYC 322)
Identity development is one of the key developmental milestones during adolescence, especially in
terms of career identity. A great deal of research has been done on the developmental progression
of how and when one develops a sense of identity. Specifically, Marcia argues that one does not
develop a clear sense of career identity until the period of emerging adulthood (Santrock, 2016).
Prior to this time there is significant variability in decidedness that one has toward one’s career.
Part of the research process is to replicate findings of other research projects in order to add
credibility to the conclusions that have been drawn. As a fellow researching scientist in the area of
adolescent development, your goal is to support or refute the age related changes in identity as
proposed by Marcia’s theory of identity development. Collect some data using the methods
described below and then write a research report supporting or refuting Marcia’s theory.
Step 1: Start by doing some background research on Marcia’s theory. Specifically, find out the basic
components of his theory and his view regarding age related changes in identity status. Also,
address the specific influences that could help a teen to develop a coherent sense of career identity.
This information can be located in your textbook.
Step 2: Once you have a good idea about the details behind his theory collect data to support his
theory. Interview at least four individuals about their future career using the interview sheet below.
At least two individuals must be teenagers between 13 and 17 years of age. At least two individuals
should be emerging adults between 18 and 25 years of age. (You may use classmates in this class for
this exercise.) Make sure to get parental consent for subjects under the age of 18 using the
consent form located on Blackboard in the Exercise Requirement Sheet. You do not need to turn
these in unless requested. You will need to turn in the answers you collected in the interview
using the Career Identity Development questions found below.
Step 3: Analyze your data by classifying each participant into one of Marcia’s identity statuses. You
will find instructions on how to do this on the last page of this assignment. Next, compare the
answers given by the younger and older participants to make a determination about developmental
differences in identity status. Think about why there might have been developmental differences in
identity status or why there were no age differences. You are looking to identify what caused the
change and getting older is not specific enough. What cognitive, biological, or social changes
occurred that brought about the change in identity? Next think about the practical implications of
this research or how you would use this information when interacting with teens.
Step 4: Next report your.

Need a nonplagiarised paper and a form completed by 1006015 before.docx

Need a nonplagiarised paper and a form completed by 10/06/015 before 7:00pm. I have attached the documents along the rubics that must be followed.
Coyne and Messina Articles, Part 2 Statistical Assessment
Details:
1) Write a paper of 1,000-1,250 words regarding the statistical significance of outcomes as presented in Messina's, et al. article "The Relationship between Patient Satisfaction and Inpatient Admissions Across Teaching and Nonteaching Hospitals."
2) Assess the appropriateness of the statistics used by referring to the chart presented in the Module 4 lecture and the resource "Statistical Assessment."
3) Discuss the value of statistical significance vs. pragmatic usefulness.
4) Prepare this assignment according to the APA guidelines found in the APA Style Guide located in the Student Success Center. An abstract is not required.
5) This assignment uses a grading rubric. Instructors will be using the rubric to grade the assignment; therefore, students should review the rubric prior to beginning the assignment to become familiar with the assignment criteria and expectations for successful completion of the assignment.
Statistics: What you Need to Know
Introduction
Often, when people begin a statistics course, they worry about doing advanced mathematics or their math phobias kick in. Understanding that statistics as addressed in this course is not a math course at all is important. The only math you will do is addition, subtraction, multiplication, and division. In these days of computer capability, you generally don't even have to do that much, since Excel is set up to do basic statistics for you. The key elements for the student in this course is to understand the various types of statistics, what their requirements are, what they do, and how you can use and interpret the results. Referring back to the basic components of a valid research study, which statistic a researcher uses depends on several things:
·
The research question itself
·
The sample size
·
The type of data you have collected
·
The type of statistic called for by the design
All quantitative studies require a data set. Qualitative studies may use a data set or may use observations with no numerical data at all. For the purposes of the next modules, our focus will be on quantitative studies.
Types of Statistics
There are several types of statistics available to the researcher. Descriptive statistics provide a basic description of the data set. This includes the measures of central tendency: means, medians, and modes, and the measures of dispersion, including variances and standard deviations. Descriptive statistics also include the sample size, or "N", and the frequency with which each data point occurs in the data set.
Inferential statistics allow the researcher to make predictions, estimations, and generalizations about the data set, the sample, and the population from which the sample was drawn. They allow you to draw inferences, generaliza.

When you are working on the Inferential Statistics Paper I want yo.docx

When you are working on the Inferential Statistics Paper I want you to format your paper with the following information
I. Introduction – What are inferential statistics and what is the research problem and hypothesis of the article?
II. Methods – Who are the subjects and variables within the article?
III. Results – What is the statistical analysis used, why were these tests chosen? What were the results of these tests and what do they mean?
IV. Discussion – What were the strengths of this article? What would you have done differently in terms of variables and statistical analysis? Why?
V. Conclusion – Reiterate the introduction and include relevant information that answers the questions regarding the hypothesis.
`
Read: Chapter 3 and 4 of Statistics for the Behavioral and Social Sciences.
Participate in One discussion.
Discussion 1 –Standard Normal Distribution– This allows you to look at any data set into the standard distribution form.
Quiz – Hypothesis testing
Submit your Inferential Statics Article Critique – Read Differential Effects of a Body Image Exposure Session on Smoking Urge Between Physically Active and Sedentary Female Smokers. What is the research question and hypothesis? Identify what variables were present, what inferential statistics were used and why, and if proper research methods were used. See grading rubric for full details.
Discussion Post Expectations:
Your initial post (your answer) is due by Day 3 (Thursday) of this week for Discussion 1.
When grading the Standard Normative Distribution discussion I will be looking for your answer to contain:
Week 2 Discussion 1 Board Rubric
Earned
Weight
Content Criteria
0.5
Student identifies and defines what Standard Normative Distribution (SND) is.
Student explains why it is needed to use a SND to compare two data sets.
0.5
Student identifies the purpose of a z-score in a SND.
0.5
Student identifies the purpose of a percentage in a SND.
0.25
Student explains whether a z-score or a percentage does a better job of identifying proportion of a SND.
0.25
The student responds to at least two classmates’ initial posts by Day 7.
1
Student uses correct spelling, grammar and sentence structure.
2
5
Grading - The discussions are both worth a total of 5 points. The breakdown of the grading for this week’s assignment (per discussion assignment) will be as follows:
Posting your answer by the due date (Day 3, Thursday) is worth 4 points. These five points will be based on the information outlined within the Discussion Assignment Expectations. Content will be worth 2 points and format; spelling and grammar will be worth 2 points.
Responding to two of your classmates (for each assignment) is worth 1 point. The answers must be substantive and go beyond “I agree” or “Good job” to qualify for this point.
Intellectual Elaboration:
In Wee.

Collecting sex disaggregated agricultural data through surveys

Presentation for the webinar on Collecting sex-disaggregated agricultural data through surveys that took place on April 21, 2016. Learn more about the webinar here: http://bit.ly/1SkWcSx
PIM Gender team members Cheryl Doss and Caitlin Kieran invited participants to discuss how the "Standards for collecting sex-disaggregated data for gender analysis" drafted by PIM in 2014 have been used to date, with a specific focus on lessons learned by CGIAR centers and external partners.
The webinar was co-organized by the CGIAR Gender and Agriculture Research Network and the CGIAR Research Program on Policies, Institutions, and Markets (PIM).

Learning Outcomes1. Describe correlations and regression a.docx

Learning Outcomes
1. Describe correlations and regression analyses.
2. Analyze the relationship between correlations and predictions.
Introduction
In contrast to Week Three where statistical tests focusing on differences were introduced, in Week Four, you will explore relationships in statistical tests. Correlations and linear regression techniques will be utilized and results will be evaluated and interpreted. The written assignments in Weeks One, Two, and Three prepared you for analyzing and evaluating research articles. In the written assignment this week, you will focus less on actual research and more on the report writing process.
If you work in a social/behavioral sciences field, you will likely be asked to conduct research (i.e., conduct an experiment or study) and create a report based on your findings. Generally speaking, people who investigate a scientific hypothesis have a responsibility to the scientific community to share those results. This is particularly true when that investigation adds to/or contradicts previous research. The research report outlines each step that was done during the research and summarizes the results and conclusions. The goal is to give the reader enough information so that the methods and results can be accurately evaluated, and the conclusions can be replicated if necessary. Although the research report this week will be based on hypothetical and/or fictitious data, the process of creating a correctly formatted research report with all the necessary components will provide you with important skills as you progress through your degree and as you continue into the world of the social/behavioral sciences.
Required Resources
Required Text
Read from the course text, Statistics for the Behavioral & Social Sciences:
· Chapter 8: Correlation
· Chapter 9: Linear Regression
Recommended Resources
Articles
1. Kirwan, J., Lounsbury, J., Gibson, L. (2010). Self-direction in learning and personality: The Big Five and narrow personality traits in relation to learner self-direction. International Journal of Self-Directed Learning, 7(2), 21-34. Retrieved from http://sdlglobal.com/IJSDL/IJSDL7.2-2010.pdf#page=25
· This is an article about personality, self-directed learning, and scale development and the major traits that may affect them. These include: agreeableness, conscientiousness, emotional stability, and openness. It incorporates correlation and regression procedures with tables that display the statistical results.
2. Stark, P.B. (2013). Chapter 9: Regression. Retrieved from http://www.stat.berkeley.edu/~stark/SticiGui/Text/regression.htm
· This website contains several video lectures and examples of how regression is used.
3. Trochim, W. M. (2006). Correlation. In Research Methods Knowledge Base. Retrieved from http://www.socialresearchmethods.net/kb/statcorr.php
· This website contains many tutorials and tools for statistical analyses and methods used in the social sciences. This pa ...

原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样

学校原件一模一样【微信：741003700 】《(unimelb毕业证书)墨尔本大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才

一比一原版斯威本理工大学毕业证（swinburne毕业证）如何办理

原版一模一样【微信：741003700 】【斯威本理工大学毕业证（swinburne毕业证）成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

Correlation and Regression Study.docx

1. The document discusses a research assignment requiring students to identify a research question from Week 1 that is suitable for a correlational study using correlation or regression analysis.
2. One example research question is "How does employees' motivation affect organizational productivity?", with motivation factors and productivity as variables that could be measured on an ordinal scale.
3. The document provides 10 total example research questions, describes their variables, and discusses appropriate measurement scales for analysis. It also lists required and recommended resources on research methods, correlation, and regression.

Community Teaching Plan Teaching Experience Paper 1Unsatisf.docx

Community Teaching Plan: Teaching Experience Paper
1
Unsatisfactory
0.00%
2
Less than Satisfactory
75.00%
3
Satisfactory
83.00%
4
Good
94.00%
5
Excellent
100.00%
80.0 %Content
30.0 %Comprehensive Summary of Teaching Plan With Epidemiological Rationale for Topic
Summary of community teaching plan is not identified or missing.
Summary of community teaching plan is incomplete.
Summary of community teaching plan is offered but some elements are vague.
Focus of community teaching is clear with a detailed summary of each component. Rationale is not provided.
Focus of community teaching is clear, consistent with Functional Health Patterns (FHP) assessment findings and supported by explanation of epidemiological rationale.
50.0 %Evaluation of Teaching Experience With Discussion of Community Response to Teaching Provided. Areas of Strength and Areas of Improvement Described
Evaluation of teaching experience is omitted or incomplete.
Evaluation of teaching experience is unclear and/or discussion of community response to teaching is missing.
Evaluation of teaching experience is provided with a brief discussion of community response to teaching.
A detailed evaluation of teaching experience with discussion of community response to teaching and areas of strength/improvement is provided.
Comprehensive evaluation of teaching experience with discussion of community response provided along with a detailed description of barriers and strategies to overcome barriers is provided.
15.0 %Organization and Effectiveness
5.0 %Thesis Development and Purpose
Paper lacks any discernible overall purpose or organizing claim.
Thesis is insufficiently developed and/or vague; purpose is not clear.
Thesis is apparent and appropriate to purpose.
Thesis is clear and forecasts the development of the paper. It is descriptive and reflective of the arguments and appropriate to the purpose.
Thesis is comprehensive; contained within the thesis is the essence of the paper. Thesis statement makes the purpose of the paper clear.
5.0 %Paragraph Development and Transitions
Paragraphs and transitions consistently lack unity and coherence. No apparent connections between paragraphs are established. Transitions are inappropriate to purpose and scope. Organization is disjointed.
Some paragraphs and transitions may lack logical progression of ideas, unity, coherence, and/or cohesiveness. Some degree of organization is evident.
Paragraphs are generally competent, but ideas may show some inconsistency in organization and/or in their relationships to each other.
A logical progression of ideas between paragraphs is apparent. Paragraphs exhibit a unity, coherence, and cohesiveness. Topic sentences and concluding remarks are appropriate to purpose.
There is a sophisticated construction of paragraphs and transitions. Ideas progress and relate to each other. Paragraph and transition construction guide the reader. Paragraph structure is seamless.
5.0 %Mechanics of Writing (includes spelling.

Nursing Research Methods Discussion Assignment.pdf

This document discusses qualitative research methods and their use in nursing research. It argues that both qualitative and quantitative research have important roles to play in evidence-based practice and improving patient outcomes. Qualitative research aims to provide rigorous analysis and thorough understanding of complex issues. The document analyzes a chosen qualitative research article on its rigor and methods. It finds the article establishes rigor through its data collection and analysis methods, which systematically generate taxonomy, themes, and theory on the research topic.

Poe_STUDY GUIDE_term 2.docx.pptx

The document outlines the topics and lectures covered in an introductory research methods course, including defining variables, developing study designs, sampling methods, data collection tools and techniques, and addressing potential biases and ethical considerations. Key areas discussed are determining sample sizes, developing quantitative and qualitative indicators, choosing sampling strategies, designing data collection instruments, and mitigating biases during the research process.

MELJUN CORTES research seminar_1__data_analysis_basics_slides

This document discusses the basics of descriptive data analysis, including defining different types of variables, coding principles, and univariate data analysis. It describes continuous variables as always numeric and categorical variables as information sorted into categories, with ordinal variables having intrinsic order, nominal variables lacking order, and dichotomous variables having only two levels. The document outlines steps for coding variables and cleaning data, as well as techniques for univariate analysis of continuous and categorical variables to check data quality.

MELJUN CORTES research seminar_1_data_analysis_basics

This document discusses the basics of descriptive data analysis, including defining different types of variables, coding principles, and univariate data analysis. It describes continuous and categorical variables, including ordinal, nominal, and dichotomous variables. The document outlines steps for coding variables and cleaning data, as well as techniques for univariate analysis of continuous and categorical variables, including examining distributions, frequencies, and comparing observed vs expected values. The goal is to familiarize readers with fundamental concepts for organizing, coding, and performing initial exploratory analysis of data.

Graduate Students’ Perceptions of Work and Family: Gender and Program Compari...

Recent political debates have suggested that the United States is on the verge of a crisis and their position as a leader in producing talented and ambitious individuals in technical professions, such as engineering, is in jeopardy. A National Academy of Sciences 2006 report stated, “the United States can no longer afford the underperformance of our academic institutions in attracting the best and brightest minds to the science and engineering enterprise. Nor can it afford to devalue the contributions of some members of that workforce through gender inequities and discrimination” (2006).
Recent years have seen the movement of women into male-predominated programs and the movement of some programs toward gender-neutral compositions. However, a study of undergraduate college women revealed that women in male-predominated programs were more likely than those in female-predominated programs to report thinking about changing their major (Steele, James, & Bartnett, 2002) indicating that there is a problem in retaining these women recruited into male-predominated programs.
This study assessed perceptions of family supportiveness in academic program and anticipated career, anticipated career barriers, gender ideology and strategies for combining career and family among 181 graduate students from male-predominated, female-predominated, and gender-neutral programs at 11 research-extensive universities in the United States. Gender and program comparisons in perceptions of family supportiveness and anticipated career barriers were examined.
Unexpectedly, students in female-predominated programs perceived their programs and future careers to be less supportive of families than students in other programs. Women also anticipated more barriers to their chosen careers than men, with a significant gender by program interaction with women in male-predominated programs anticipating the most severe career barriers. While an egalitarian gender ideology was found to be a significant predictor of career scaling back for women it was not associated with career scaling back for men.

© 2016 Laureate Education, Inc. 1 of 3 SOCW 6301 W.docx

© 2016 Laureate Education, Inc. 1 of 3
SOCW 6301: Week 10 Assignment Guidelines
Quantitative Article Review and Critique
In approximately 7-10 pages (including title page and references), address the
following questions.
Title
After reading the entire article, do you think the title adequately describes
the study? Does the title catch your attention? Please explain.
Abstract
Does the abstract contain the recommended content (see “Abstract,”
pp. 314, in Yegidis et al.)? How difficult do you think it is to
summarize so much information in 150–250 words? Please explain.
Introduction
Why did the authors conduct this study and write this article? What was the
problem of interest or concern? Be specific. Use quotes and paraphrases
with citations. What audience might be interested in this study?
Do you feel the problem is significant enough to warrant a journal article?
Did you have a “so what” reaction? If so, why do you think it was accepted
for publication? Please justify your position.
To what extent does the literature presented in the introduction help you
understand the problem? How does the literature reviewed put the problem
in context? Be specific.
Does the researcher indicate how this research is different from and/or
similar to earlier ones reported in the literature? Summarize what this
article intends to add to the knowledge base.
Do the authors state their research questions and/or hypotheses? What
are the hypotheses or focused research questions?
Methods
What specific quantitative method is used? How does a quantitative
research design correspond with the research questions or hypotheses?
Can you determine whether the design was appropriate?
© 2016 Laureate Education, Inc. 2 of 3
To what extent can the design answer the research questions or
address the stated hypotheses? Elaborate.
What were the variables under study? If relevant, identify the main dependent
and independent variables. If not relevant, why are there no dependent and
independent variables? What instruments or observations were used in the
research? Explain why you do, or do not, think that the methods used to
collect the data are described clearly enough to allow for replication. Be
specific and please elaborate.
Explain whether or not information was provided concerning the reliability and
validity of these instruments or observations. Was this information adequate?
How does the presence or absence of information about reliability and validity
affect your confidence in the quality of the study? What have the authors
done to address or strengthen internal validity? Be specific.
Sample
How were the participants recruited or selected for the study? What sampling
strategy was used? Is the sample large enough to address the hypotheses
and research questions? Did the author(s) offer any justification for the
sample size? Are you satisfied with the in.

Strategic Management and Organizational Change 1Unsatisfacto.docx

Strategic Management and Organizational Change
1
Unsatisfactory
0.00%
2
Less than Satisfactory
65.00%
3
Satisfactory
75.00%
4
Good
85.00%
5
Excellent
100.00%
100.0 %Content
40.0 %Address Types of Health Care Organizational Structure, Including How the Type of Structure Impacts the Process and Effectiveness of Change
Does not demonstrate understanding of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Does not demonstrate critical thinking and analysis of the distinction between organizational and transformational change, and does not include examples or descriptions.
Demonstrates only minimal understanding of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Demonstrates only minimal abilities for making the distinction between organizational and transformational change, and does not include examples or descriptions.
Demonstrates knowledge of health care organizational structure and how the type of structure impacts the process and effectiveness of change, but has some slight misunderstanding of the distinction between organizational and transformational change. Provides a basic idea of critical thinking and analysis for the questions, answers, and rationale. Does not include examples or descriptions.
Demonstrates acceptable knowledge of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Develops an acceptable distinction between organizational and transformational change. Utilizes some examples of leadership models, tools, and advice.
Demonstrates thorough knowledge of health care organizational structure and how the type of structure impacts the process and effectiveness of change. Clearly differentiates between organizational and transformational change. Introduces appropriate examples of leadership models, tools, and advice.
30.0 %Integrates Information From Outside Resources Into the Body of Paper
Does not use references, examples, or explanations.
Provides some supporting examples, but minimal explanations and no published references.
Supports main points with examples and explanations, but fails to include published references to support claims and ideas.
Supports main points with references, explanations, and examples. Analysis and description is direct, competent, and appropriate of the criteria.
Supports main points with references, examples, and full explanations of how they apply. Thoughtfully, analyzes, evaluates, and describes major points of the criteria.
7.0 %Assignment Development and Purpose
Paper lacks any discernible overall purpose or organizing claim.
Thesis and/or main claim are insufficiently developed and/or vague; purpose is not clear.
Thesis and/or main claim are apparent and appropriate to purpose.
Thesis and/or main claim are clear and forecast the development of the paper. It is descriptive and reflective.

1 Crosstabs Lesson 1 Running crosstabs to test you.docx

1
Crosstabs
Lesson 1: Running crosstabs to test your hypothesis
To access the Crosstabs in your SPSS, click the following:
Analyze Descriptive Statistics Crosstabs
Once you work your way through these selections, you should reach this dialog box:
You will want to place your dependent variable in the row variable and your independent variable in the
column variable. For this example, we will use AFFRMACT (preference for affirmative action policies) for
the dependent variable and SEX (gender of the respondent) as the independent variable.
2
Now we want to tell SPSS to compute the column percentages. To do this you will choose ‘Cells’ and
then select ‘Column’ in the “Percentages” box; then click ‘Continue’.
Now select ‘OK’ to run your crosstabs. You should get the following results:
3
Lesson 2: Examining Your Output
We just ran crosstabs to test a hypothesis with two variables, one nominal (SEX-independent variable)
and one ordinal (AFFRMACT-dependent variable). As you can see, the categories of the independent
variable are found across the top in the columns and the dependent variable information is found down
the side forming the rows. Each square is known as a cell and within each cell is the frequency (or
count) and the column percentage. You can also find the row totals and column totals, which are
sometimes referred to as marginal.
In our example we know the following is true:
7.8% of men in this sample strongly support affirmative action policies, whereas 11.4% of
women do;
We can also look at grouping at a glance and concede that 15% of men and 18.5% of women
support affirmative action policies in comparison to 84.9% of men and 81.5% of women oppose
these policies.
The bottom right cell in the table is where we can find that we had 1,904 people answer this
question as our sample.
Lesson 3: Interpreting Crosstabs
Researchers run crosstabs to determine whether there is an association between two variables. Also,
crosstabs may tell us other important things about the relationship between the two variables, including
the strength of association, and sometimes the direction of the association. FYI, the direction can only
be found when both of the variables in your table are greater than nominal.
Ask yourself the following questions after you populate your crosstabs:
1. Is there an association between the two variables?
If you answer yes to this (or maybe), then move to question 2.
2. What is the strength of association between the two variables?
If BOTH variables are ordinal than move to question 3.
3. What is the direction of association?
Is there an association?
What we are trying to determine here is whether knowing the value of one variable will help us predict
the value of another variable. In other words, if gender is associated with preference to affirmative
action policies. In orde ...

Research Critique of a Published Quantitative Research.docx

The study aimed to evaluate women's experiences of postnatal distress during the first year after childbirth. Semi-structured interviews were conducted with 17 women who had experienced psychological issues after giving birth. The interviews were analyzed using Interpretative Phenomenological Analysis. The results indicated that women experience various emotional difficulties following childbirth, associated with adjusting to their new role as mothers. The study provides insights that could help improve support for women after childbirth.

POLI_399_tutorial_4

This document discusses causal modeling and how to establish causal relationships between variables. It provides examples of different types of causal models, including an intervening variable model and a source of spuriousness model. Guidelines are given for including key elements in a causal model such as labeling variables, indicating the direction of relationships, and incorporating intervening or antecedent variables from the literature. The document also demonstrates how to construct causal models using Microsoft Word.

Assessment 1PRINTAnalysis of Position Papers for Vulnerabl.docx

The document provides instructions for an assessment requiring students to analyze position papers on a health care issue related to a vulnerable population. Students must explain their position on the issue, the role of an interprofessional team, and evaluate supporting and opposing evidence and positions. The analysis should be 4-6 pages, cite 3-5 supporting and 2-3 opposing sources, and follow APA style formatting. The target population and issue will be used for future assessments to potentially create a new policy.

Stat11t Chapter1

This document provides an overview of key concepts from Chapter 1 of the textbook "Elementary Statistics". It defines important statistical terms like population, sample, parameter, and statistic. It also distinguishes between different types of data and levels of measurement. Additionally, it discusses the importance of collecting sample data through appropriate random sampling methods. Critical thinking in statistics is emphasized, highlighting factors like the context, source, and sampling method of data when evaluating statistical claims. Different ways of collecting data through studies and experiments are also introduced.

Stat11t chapter1

The document summarizes key concepts from Chapter 1 of the textbook "Elementary Statistics" including:
- The difference between a population and a sample, and how statistics uses samples to make inferences about populations.
- The different types of data: quantitative, categorical, discrete vs. continuous data.
- The different levels of measurement for data: nominal, ordinal, interval, and ratio.
- The importance of critical thinking when analyzing data and statistics, including considering context, sources, sampling methods, and avoiding misleading graphs, samples, conclusions, or survey questions.

Exercise Identity Development in Adolescence Psychology of .docx

Exercise: Identity Development in Adolescence
Psychology of Adolescence (PSYC 322)
Identity development is one of the key developmental milestones during adolescence, especially in
terms of career identity. A great deal of research has been done on the developmental progression
of how and when one develops a sense of identity. Specifically, Marcia argues that one does not
develop a clear sense of career identity until the period of emerging adulthood (Santrock, 2016).
Prior to this time there is significant variability in decidedness that one has toward one’s career.
Part of the research process is to replicate findings of other research projects in order to add
credibility to the conclusions that have been drawn. As a fellow researching scientist in the area of
adolescent development, your goal is to support or refute the age related changes in identity as
proposed by Marcia’s theory of identity development. Collect some data using the methods
described below and then write a research report supporting or refuting Marcia’s theory.
Step 1: Start by doing some background research on Marcia’s theory. Specifically, find out the basic
components of his theory and his view regarding age related changes in identity status. Also,
address the specific influences that could help a teen to develop a coherent sense of career identity.
This information can be located in your textbook.
Step 2: Once you have a good idea about the details behind his theory collect data to support his
theory. Interview at least four individuals about their future career using the interview sheet below.
At least two individuals must be teenagers between 13 and 17 years of age. At least two individuals
should be emerging adults between 18 and 25 years of age. (You may use classmates in this class for
this exercise.) Make sure to get parental consent for subjects under the age of 18 using the
consent form located on Blackboard in the Exercise Requirement Sheet. You do not need to turn
these in unless requested. You will need to turn in the answers you collected in the interview
using the Career Identity Development questions found below.
Step 3: Analyze your data by classifying each participant into one of Marcia’s identity statuses. You
will find instructions on how to do this on the last page of this assignment. Next, compare the
answers given by the younger and older participants to make a determination about developmental
differences in identity status. Think about why there might have been developmental differences in
identity status or why there were no age differences. You are looking to identify what caused the
change and getting older is not specific enough. What cognitive, biological, or social changes
occurred that brought about the change in identity? Next think about the practical implications of
this research or how you would use this information when interacting with teens.
Step 4: Next report your.

Need a nonplagiarised paper and a form completed by 1006015 before.docx

Need a nonplagiarised paper and a form completed by 10/06/015 before 7:00pm. I have attached the documents along the rubics that must be followed.
Coyne and Messina Articles, Part 2 Statistical Assessment
Details:
1) Write a paper of 1,000-1,250 words regarding the statistical significance of outcomes as presented in Messina's, et al. article "The Relationship between Patient Satisfaction and Inpatient Admissions Across Teaching and Nonteaching Hospitals."
2) Assess the appropriateness of the statistics used by referring to the chart presented in the Module 4 lecture and the resource "Statistical Assessment."
3) Discuss the value of statistical significance vs. pragmatic usefulness.
4) Prepare this assignment according to the APA guidelines found in the APA Style Guide located in the Student Success Center. An abstract is not required.
5) This assignment uses a grading rubric. Instructors will be using the rubric to grade the assignment; therefore, students should review the rubric prior to beginning the assignment to become familiar with the assignment criteria and expectations for successful completion of the assignment.
Statistics: What you Need to Know
Introduction
Often, when people begin a statistics course, they worry about doing advanced mathematics or their math phobias kick in. Understanding that statistics as addressed in this course is not a math course at all is important. The only math you will do is addition, subtraction, multiplication, and division. In these days of computer capability, you generally don't even have to do that much, since Excel is set up to do basic statistics for you. The key elements for the student in this course is to understand the various types of statistics, what their requirements are, what they do, and how you can use and interpret the results. Referring back to the basic components of a valid research study, which statistic a researcher uses depends on several things:
·
The research question itself
·
The sample size
·
The type of data you have collected
·
The type of statistic called for by the design
All quantitative studies require a data set. Qualitative studies may use a data set or may use observations with no numerical data at all. For the purposes of the next modules, our focus will be on quantitative studies.
Types of Statistics
There are several types of statistics available to the researcher. Descriptive statistics provide a basic description of the data set. This includes the measures of central tendency: means, medians, and modes, and the measures of dispersion, including variances and standard deviations. Descriptive statistics also include the sample size, or "N", and the frequency with which each data point occurs in the data set.
Inferential statistics allow the researcher to make predictions, estimations, and generalizations about the data set, the sample, and the population from which the sample was drawn. They allow you to draw inferences, generaliza.

When you are working on the Inferential Statistics Paper I want yo.docx

When you are working on the Inferential Statistics Paper I want you to format your paper with the following information
I. Introduction – What are inferential statistics and what is the research problem and hypothesis of the article?
II. Methods – Who are the subjects and variables within the article?
III. Results – What is the statistical analysis used, why were these tests chosen? What were the results of these tests and what do they mean?
IV. Discussion – What were the strengths of this article? What would you have done differently in terms of variables and statistical analysis? Why?
V. Conclusion – Reiterate the introduction and include relevant information that answers the questions regarding the hypothesis.
`
Read: Chapter 3 and 4 of Statistics for the Behavioral and Social Sciences.
Participate in One discussion.
Discussion 1 –Standard Normal Distribution– This allows you to look at any data set into the standard distribution form.
Quiz – Hypothesis testing
Submit your Inferential Statics Article Critique – Read Differential Effects of a Body Image Exposure Session on Smoking Urge Between Physically Active and Sedentary Female Smokers. What is the research question and hypothesis? Identify what variables were present, what inferential statistics were used and why, and if proper research methods were used. See grading rubric for full details.
Discussion Post Expectations:
Your initial post (your answer) is due by Day 3 (Thursday) of this week for Discussion 1.
When grading the Standard Normative Distribution discussion I will be looking for your answer to contain:
Week 2 Discussion 1 Board Rubric
Earned
Weight
Content Criteria
0.5
Student identifies and defines what Standard Normative Distribution (SND) is.
Student explains why it is needed to use a SND to compare two data sets.
0.5
Student identifies the purpose of a z-score in a SND.
0.5
Student identifies the purpose of a percentage in a SND.
0.25
Student explains whether a z-score or a percentage does a better job of identifying proportion of a SND.
0.25
The student responds to at least two classmates’ initial posts by Day 7.
1
Student uses correct spelling, grammar and sentence structure.
2
5
Grading - The discussions are both worth a total of 5 points. The breakdown of the grading for this week’s assignment (per discussion assignment) will be as follows:
Posting your answer by the due date (Day 3, Thursday) is worth 4 points. These five points will be based on the information outlined within the Discussion Assignment Expectations. Content will be worth 2 points and format; spelling and grammar will be worth 2 points.
Responding to two of your classmates (for each assignment) is worth 1 point. The answers must be substantive and go beyond “I agree” or “Good job” to qualify for this point.
Intellectual Elaboration:
In Wee.

Collecting sex disaggregated agricultural data through surveys

Presentation for the webinar on Collecting sex-disaggregated agricultural data through surveys that took place on April 21, 2016. Learn more about the webinar here: http://bit.ly/1SkWcSx
PIM Gender team members Cheryl Doss and Caitlin Kieran invited participants to discuss how the "Standards for collecting sex-disaggregated data for gender analysis" drafted by PIM in 2014 have been used to date, with a specific focus on lessons learned by CGIAR centers and external partners.
The webinar was co-organized by the CGIAR Gender and Agriculture Research Network and the CGIAR Research Program on Policies, Institutions, and Markets (PIM).

Learning Outcomes1. Describe correlations and regression a.docx

Learning Outcomes
1. Describe correlations and regression analyses.
2. Analyze the relationship between correlations and predictions.
Introduction
In contrast to Week Three where statistical tests focusing on differences were introduced, in Week Four, you will explore relationships in statistical tests. Correlations and linear regression techniques will be utilized and results will be evaluated and interpreted. The written assignments in Weeks One, Two, and Three prepared you for analyzing and evaluating research articles. In the written assignment this week, you will focus less on actual research and more on the report writing process.
If you work in a social/behavioral sciences field, you will likely be asked to conduct research (i.e., conduct an experiment or study) and create a report based on your findings. Generally speaking, people who investigate a scientific hypothesis have a responsibility to the scientific community to share those results. This is particularly true when that investigation adds to/or contradicts previous research. The research report outlines each step that was done during the research and summarizes the results and conclusions. The goal is to give the reader enough information so that the methods and results can be accurately evaluated, and the conclusions can be replicated if necessary. Although the research report this week will be based on hypothetical and/or fictitious data, the process of creating a correctly formatted research report with all the necessary components will provide you with important skills as you progress through your degree and as you continue into the world of the social/behavioral sciences.
Required Resources
Required Text
Read from the course text, Statistics for the Behavioral & Social Sciences:
· Chapter 8: Correlation
· Chapter 9: Linear Regression
Recommended Resources
Articles
1. Kirwan, J., Lounsbury, J., Gibson, L. (2010). Self-direction in learning and personality: The Big Five and narrow personality traits in relation to learner self-direction. International Journal of Self-Directed Learning, 7(2), 21-34. Retrieved from http://sdlglobal.com/IJSDL/IJSDL7.2-2010.pdf#page=25
· This is an article about personality, self-directed learning, and scale development and the major traits that may affect them. These include: agreeableness, conscientiousness, emotional stability, and openness. It incorporates correlation and regression procedures with tables that display the statistical results.
2. Stark, P.B. (2013). Chapter 9: Regression. Retrieved from http://www.stat.berkeley.edu/~stark/SticiGui/Text/regression.htm
· This website contains several video lectures and examples of how regression is used.
3. Trochim, W. M. (2006). Correlation. In Research Methods Knowledge Base. Retrieved from http://www.socialresearchmethods.net/kb/statcorr.php
· This website contains many tutorials and tools for statistical analyses and methods used in the social sciences. This pa ...

Correlation and Regression Study.docx

Correlation and Regression Study.docx

Community Teaching Plan Teaching Experience Paper 1Unsatisf.docx

Community Teaching Plan Teaching Experience Paper 1Unsatisf.docx

Nursing Research Methods Discussion Assignment.pdf

Nursing Research Methods Discussion Assignment.pdf

Poe_STUDY GUIDE_term 2.docx.pptx

Poe_STUDY GUIDE_term 2.docx.pptx

MELJUN CORTES research seminar_1__data_analysis_basics_slides

MELJUN CORTES research seminar_1__data_analysis_basics_slides

MELJUN CORTES research seminar_1_data_analysis_basics

MELJUN CORTES research seminar_1_data_analysis_basics

Graduate Students’ Perceptions of Work and Family: Gender and Program Compari...

Graduate Students’ Perceptions of Work and Family: Gender and Program Compari...

© 2016 Laureate Education, Inc. 1 of 3 SOCW 6301 W.docx

© 2016 Laureate Education, Inc. 1 of 3 SOCW 6301 W.docx

Strategic Management and Organizational Change 1Unsatisfacto.docx

Strategic Management and Organizational Change 1Unsatisfacto.docx

1 Crosstabs Lesson 1 Running crosstabs to test you.docx

1 Crosstabs Lesson 1 Running crosstabs to test you.docx

Research Critique of a Published Quantitative Research.docx

Research Critique of a Published Quantitative Research.docx

POLI_399_tutorial_4

POLI_399_tutorial_4

Assessment 1PRINTAnalysis of Position Papers for Vulnerabl.docx

Assessment 1PRINTAnalysis of Position Papers for Vulnerabl.docx

Stat11t Chapter1

Stat11t Chapter1

Stat11t chapter1

Stat11t chapter1

Exercise Identity Development in Adolescence Psychology of .docx

Exercise Identity Development in Adolescence Psychology of .docx

Need a nonplagiarised paper and a form completed by 1006015 before.docx

Need a nonplagiarised paper and a form completed by 1006015 before.docx

When you are working on the Inferential Statistics Paper I want yo.docx

When you are working on the Inferential Statistics Paper I want yo.docx

Collecting sex disaggregated agricultural data through surveys

Collecting sex disaggregated agricultural data through surveys

Learning Outcomes1. Describe correlations and regression a.docx

Learning Outcomes1. Describe correlations and regression a.docx

原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样

学校原件一模一样【微信：741003700 】《(unimelb毕业证书)墨尔本大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才

一比一原版斯威本理工大学毕业证（swinburne毕业证）如何办理

原版一模一样【微信：741003700 】【斯威本理工大学毕业证（swinburne毕业证）成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理斯威本理工大学毕业证（swinburne毕业证）【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

社内勉強会資料_Hallucination of LLMs .

社内エンジニア・リサーチャー勉強会の発表資料「Hallucination of LLMs」を公開しました！
大規模言語モデル(LLM)に起こるハルシネーションのメカニズムと、それらを軽減する方法について紹介しています。

原版一比一多伦多大学毕业证(UofT毕业证书)如何办理

原版制作【微信:41543339】【多伦多大学毕业证(UofT毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

一比一原版南十字星大学毕业证(SCU毕业证书)学历如何办理

原版办理【微信号:BYZS866】【南十字星大学毕业证(SCU毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号BYZS866】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号BYZS866】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理

原版制作【微信:41543339】【爱尔兰都柏林大学毕业证(UCD毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

Cell The Unit of Life for NEET Multiple Choice Questions.docx

celltheunitoflife
ribosomes
thegolgi
nuclearmembrane
cilia
phragmoplast

End-to-end pipeline agility - Berlin Buzzwords 2024

We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.

一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理

原版制作【微信:41543339】【(Sheffield毕业证书)谢菲尔德大学毕业证】【微信:41543339】《成绩单、外壳、雅思、offer、留信学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器一制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

一比一原版加拿大渥太华大学毕业证（uottawa毕业证书）如何办理

原版一模一样【微信：741003700 】【渥太华大学毕业证（uottawa毕业证书）成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理渥太华大学毕业证（uottawa毕业证书）【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理渥太华大学毕业证（uottawa毕业证书）【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理渥太华大学毕业证（uottawa毕业证书）【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理渥太华大学毕业证（uottawa毕业证书）【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

一比一原版莱斯大学毕业证（rice毕业证）如何办理

原版一模一样【微信：741003700 】【莱斯大学毕业证（rice毕业证）成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理莱斯大学毕业证（rice毕业证）【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理莱斯大学毕业证（rice毕业证）【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理莱斯大学毕业证（rice毕业证）【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理莱斯大学毕业证（rice毕业证）【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024

We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of May 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.

Build applications with generative AI on Google Cloud

We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.

The Ipsos - AI - Monitor 2024 Report.pdf

According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...

This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!

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一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理

原版一模一样【微信：741003700 】【(曼大毕业证书)曼尼托巴大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理(曼大毕业证书)曼尼托巴大学毕业证【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理(曼大毕业证书)曼尼托巴大学毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理(曼大毕业证书)曼尼托巴大学毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理(曼大毕业证书)曼尼托巴大学毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

一比一原版南昆士兰大学毕业证如何办理

原版一模一样【微信：741003700 】【南昆士兰大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理南昆士兰大学毕业证【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理南昆士兰大学毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理南昆士兰大学毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理南昆士兰大学毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理

原版一模一样【微信：741003700 】【(uom毕业证书)曼彻斯特大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理(uom毕业证书)曼彻斯特大学毕业证【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理(uom毕业证书)曼彻斯特大学毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理(uom毕业证书)曼彻斯特大学毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理(uom毕业证书)曼彻斯特大学毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

一比一原版马来西亚博特拉大学毕业证（upm毕业证）如何办理

原版一模一样【微信：741003700 】【马来西亚博特拉大学毕业证（upm毕业证）成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理马来西亚博特拉大学毕业证（upm毕业证）【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理马来西亚博特拉大学毕业证（upm毕业证）【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理马来西亚博特拉大学毕业证（upm毕业证）【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理马来西亚博特拉大学毕业证（upm毕业证）【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

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原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样

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一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理

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- 1. Organizing data in tables and charts: Criteria for effective presentation Jane E. Miller, Ph.D. Rutgers University
- 2. About the author Author: The Chicago Guide to Writing about Multivariate Analysis (Chicago, 2005) and The Chicago Guide to Writing about Numbers (Chicago, 2004), and other articles about statistical literacy and quantitative communication. Professor, Rutgers University Institute for Health, Health Care Policy and Aging Research. Edward J. Bloustein School of Planning and Public Policy.
- 3. Learning objectives To learn the different types of variables and how they affect choices for organizing data. To become aware of different principles for organizing variables in tables or charts. To learn the strengths and weaknesses of tables, charts, and prose for organizing and conveying numeric information.
- 4. Performance objectives To be able to choose among different criteria for organizing data for a particular task. To be able to identify whether to use a table or chart to present data for a specific objective. To understand how to write a prose description to coordinate with a table or chart.
- 5. Why does order of variables matter? The arrangement of items in a table or chart should coordinate with order they are mentioned in the prose description. Avoid zigzagging back and forth across a chart or among rows and columns of a table. Usually describe a pattern based on observed numeric values, e.g., most to least common. Often a hypothesis includes some theoretical basis of how items relate to one another.
- 6. Ordinal and continuous variables Values of ordinal, interval, and ratio variables have an inherent numeric order. E.g., age groups, dates, blood pressure. Numeric or chronological order of values is the principle for organizing those values in a table or chart.
- 7. Nominal variables Values of nominal variables have no inherent numeric order. E.g., categories of race, gender, or region. Need an organizing principle to determine sequence of items. Same issue if you have >1 variable to present. Several different causes of death. Prevalence of >1 symptoms, attitudes, etc.
- 8. + and - of different tools Strengths Weaknesses Prose Easiest way to explain patterns Hard to organize a lot of numbers Table Holds lots of #s Good for detail Predictable structure Harder to "see" patterns Chart Holds lots of #s Easy to see general patterns Predictable structure Difficult to see specific values
- 9. Complementary use of prose, tables & charts Use tables and charts to present full set of numeric values. Use prose to describe the pattern or address the hypothesis. Use same ordering principle in table or chart and its accompanying prose. Improves clarity of narrative line.
- 10. Prose description of a pattern Objectives: Describe size and shape of the pattern. Explain whether it matches hypothesis. Specify direction and magnitude of association. Direction: “Which is higher? Magnitude: “How much higher?”
- 11. Direction for different types of variables Direction for ordinal, interval or ratio variable: Is the relationship positive, negative, or level? E.g., as income rises, do death rates increase, decrease or remain constant? For nominal variables: Which category has the highest value? E.g., which gender has the higher death rate?
- 12. Principles for organizing data Alphabetical order Order of items on original data collection instrument Empirical order Theoretical groupings Arbitrary order – NEVER a good idea! Think about how the data will be used, and choose one of the above principles!
- 13. For tables and charts accompanied by prose Pattern description or hypothesis testing
- 14. Example: Attitudes about legal abortion “Please tell me whether or not you think it should be possible for a pregnant woman to obtain a legal abortion” % of respondents who agree If the woman wants it for any reason 43.7 If there is a strong chance of defect in the baby 79.8 If the woman's own health is seriously endangered by the pregnancy 88.2 If she is not married and does not want to marry the man 42.5 If she becomes pregnant as a result of rape 80.8 If she is married and does not want any more children 44.4 From the 2000 U.S. General Social Survey
- 15. Order of items from questionnaire Agreement with legal abortion under specified circumstances, 2000 U.S. General Social Survey 0 20 40 60 80 100 Any reason Defect in baby Wants no more kids Mother's health Pregnant due to rape Not married % of respondents
- 16. Order of items from questionnaire Agreement with legal abortion under specified circumstances, 2000 U.S. General Social Survey 0 20 40 60 80 100 Any reason Defect in baby Wants no more kids Mother's health Pregnant due to rape Not married % of respondents
- 17. Alphabetical order Agreement with legal abortion under specified circumstances, 2000 U.S. General Social Survey 0 20 40 60 80 100 Any reason Defect in baby Mother's health Not married Rape Wants no more % of respondents
- 18. Empirical order (descending) Agreement with legal abortion under specified circumstances, 2000 U.S. General Social Survey 0 20 40 60 80 100 Mother's health Rape Defect in baby Wants no more Any reason Not married % of respondents
- 19. Theoretical grouping Agreement with legal abortion under specified circumstances, 2000 U.S. General Social Survey 0 20 40 60 80 100 Mother's health* Pregnant due to rape* Defect in baby* Wants no more kids Any reason Not married % of respondents Health reasons Social reasons
- 20. Theoretical grouping Agreement with legal abortion under specified circumstances, 2000 U.S. General Social Survey 0 20 40 60 80 100 Mother's health* Pregnant due to rape* Defect in baby* Wants no more kids Any reason Not married % of respondents Health reasons Social reasons
- 21. Combining theoretical & empirical criteria Descending dollar value of expenditures for necessities and non-necessities, 2002 U.S. Consumer Expenditure Survey $- $3,000 $6,000 $9,000 $12,000 $15,000 S h e l t e r + u t i l i t i e s F o o d A p p a r e l a n d s e r v i c e s T r a n s p o r t a t i o n P e r s o n a l i n s & p e n s i o n s A l l o t h e r h o u s i n g H e a l t h c a r e E n t e r t a i n m e n t C a s h c o n t r i b u t i o n s M i s c e l l a n e o u s E d u c a t i o n P e r s o n a l c a r e A l c o h o l i c b e v e r a g e s T o b a c c o p r o d u c t s R e a d i n g Necessities Non-necessities
- 22. Pattern with a third variable Agreement with legal abortion, by gender of respondent and circumstances of abortion, 2000 U.S. General Social Survey Organized by topic of abortion question 0 20 40 60 80 100 Mother's health* Pregnant due to rape* Defect in baby* Wants no more kids Any reason Not married % of respondents Men Women Health reasons Social reasons * difference between men and women is statistically significant at p<.05
- 23. Pattern with a third variable Agreement with legal abortion, by gender of respondent and circumstances of abortion, 2000 U.S. General Social Survey Organized by topic of abortion question 0 20 40 60 80 100 Mother's health* Pregnant due to rape* Defect in baby* Wants no more kids Any reason Not married % of respondents Men Women Health reasons Social reasons * difference between men and women is statistically significant at p<.05
- 24. Identifying theoretical criteria Consult the published literature on your topic to learn about theoretical criteria for organizing your variables. In new research areas, empirical sorting may yield clusters with similar response patterns that can then be explored for conceptual overlap.
- 25. For self-guided data lookup Why is it important? When is it used? Researchers look up data for own research questions, then organize the data using empirical or theoretical criteria. How to organize data for such tasks? Alphabetical order Order of items from data collection instrument Standard ordering used in periodic reports
- 26. Alphabetical order Widely familiar principle, e.g., used in Phone book Daily stock market report Learned at an early age Facilitates self-guided lookup
- 27. Ordering for a public data source Order of items on original data collection instrument Users can refer to codebook Easy to find the variables they need Ordering used in periodic reports Standardized from year to year for a given topic
- 28. Summary There is no one principle for organizing numeric data that fits all possible tasks. Determine your main objective Hypothesis testing or pattern description Data reporting for others’ use Choose the organizing principle accordingly.