analysis
•Download as PPT, PDF•
0 likes•300 views
This document provides guidance on analyzing results for an investigation. It recommends describing and explaining each set of results, making links between different results, and relating all results back to the original title and objectives to prove or disprove the initial question or hypothesis. The analysis should directly quote data from traffic counts, surveys, and other sources to support the descriptions and explanations.
Report
Share
Report
Share
![[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Questionnaire analysis using_spss
The document discusses key considerations for designing questionnaires, including:
1. The format of questions will affect the answers, so questions should be short (under 25 words), understandable, and avoid double negatives.
2. Choosing an appropriate question format is important so responses are understandable and analyzable. Questions types include single answers, multiple choices, scales, and grids.
3. Pilot testing the questionnaire is essential to check that the data can be analyzed as intended and to refine ambiguous, leading, or poorly structured questions. Feedback from pilot participants should be solicited.
4. Generally, questionnaires should be limited to around 20 likert-scale questions to maintain participant interest and engagement. A variety of
Factor Analysis and Correspondence Analysis Composite and Indicator Scores of...
Factor analysis and correspondence analysis can be used to generate composite and indicator scores from Likert scale survey data. This allows researchers to distill survey responses down into relevant information about populations and attitudes. The document demonstrates how to calculate these scores in four steps for both factor analysis and correspondence analysis. It also compares the advantages and disadvantages of each method and how the analysis can help organizations think differently about survey data.
Levels of measurement discuss
This document discusses the four levels of measurement for data: nominal, ordinal, interval, and ratio. Nominal data involves qualitative categories without order. Ordinal data involves ordered categories but without measurable differences. Interval data involves ordered categories with measurable differences but no defined zero point. Ratio data involves ordered categories with measurable differences and a defined zero point, allowing calculations of ratios. Examples are provided for each level of measurement.
Quantitative data analysis
This document outlines key concepts in statistics that are important for social science research. It discusses research design, collecting and organizing data, different variable types, descriptive statistics like measures of central tendency and dispersion, cross-tabulations, and correlation. The goal is to equip students with the statistical literacy needed to analyze and report on their research results.
Ib ess guidelines for lab design
This document provides guidelines and templates for designing an experiment for an IB Extended Essay in Sciences. It instructs students to state a clear research question and hypothesis, define the independent and dependent variables, control for confounding variables, develop a method for collecting sufficient and relevant data, and process the data for analysis. Tables are provided to help students document the independent variable levels, dependent variable measurements, and controlled variables for their experimental design.
ESS Internal Assessment Rubric
Scoring rubric for Internal Assessments (IA)s in the IBDP Environmental Systems and Societies course.
Factor analysis (1)
Exploratory factor analysis (EFA) is a statistical technique used to identify the underlying relationships between measured variables. EFA can group variables into a smaller number of factors and reduce complexity in the data. The document discusses EFA methodology, including conducting EFA in SPSS, determining the number of factors, rotating factors, and interpreting results. Assumptions of EFA and different extraction and rotation methods are also covered.
Interval data
This document discusses different types of data and which statistical tests are appropriate for each. It defines nominal, categorical, ordinal, interval, and ratio data, explaining the key properties and differences between each. The document concludes that it is important to understand the level of measurement of your data in order to select the correct parametric or non-parametric statistical test to use. Non-parametric tests make fewer assumptions than parametric tests but can be less powerful.
Recommended
Questionnaire analysis using_spss
The document discusses key considerations for designing questionnaires, including:
1. The format of questions will affect the answers, so questions should be short (under 25 words), understandable, and avoid double negatives.
2. Choosing an appropriate question format is important so responses are understandable and analyzable. Questions types include single answers, multiple choices, scales, and grids.
3. Pilot testing the questionnaire is essential to check that the data can be analyzed as intended and to refine ambiguous, leading, or poorly structured questions. Feedback from pilot participants should be solicited.
4. Generally, questionnaires should be limited to around 20 likert-scale questions to maintain participant interest and engagement. A variety of
Factor Analysis and Correspondence Analysis Composite and Indicator Scores of...
Factor analysis and correspondence analysis can be used to generate composite and indicator scores from Likert scale survey data. This allows researchers to distill survey responses down into relevant information about populations and attitudes. The document demonstrates how to calculate these scores in four steps for both factor analysis and correspondence analysis. It also compares the advantages and disadvantages of each method and how the analysis can help organizations think differently about survey data.
Levels of measurement discuss
This document discusses the four levels of measurement for data: nominal, ordinal, interval, and ratio. Nominal data involves qualitative categories without order. Ordinal data involves ordered categories but without measurable differences. Interval data involves ordered categories with measurable differences but no defined zero point. Ratio data involves ordered categories with measurable differences and a defined zero point, allowing calculations of ratios. Examples are provided for each level of measurement.
Quantitative data analysis
This document outlines key concepts in statistics that are important for social science research. It discusses research design, collecting and organizing data, different variable types, descriptive statistics like measures of central tendency and dispersion, cross-tabulations, and correlation. The goal is to equip students with the statistical literacy needed to analyze and report on their research results.
Ib ess guidelines for lab design
This document provides guidelines and templates for designing an experiment for an IB Extended Essay in Sciences. It instructs students to state a clear research question and hypothesis, define the independent and dependent variables, control for confounding variables, develop a method for collecting sufficient and relevant data, and process the data for analysis. Tables are provided to help students document the independent variable levels, dependent variable measurements, and controlled variables for their experimental design.
ESS Internal Assessment Rubric
Scoring rubric for Internal Assessments (IA)s in the IBDP Environmental Systems and Societies course.
Factor analysis (1)
Exploratory factor analysis (EFA) is a statistical technique used to identify the underlying relationships between measured variables. EFA can group variables into a smaller number of factors and reduce complexity in the data. The document discusses EFA methodology, including conducting EFA in SPSS, determining the number of factors, rotating factors, and interpreting results. Assumptions of EFA and different extraction and rotation methods are also covered.
Interval data
This document discusses different types of data and which statistical tests are appropriate for each. It defines nominal, categorical, ordinal, interval, and ratio data, explaining the key properties and differences between each. The document concludes that it is important to understand the level of measurement of your data in order to select the correct parametric or non-parametric statistical test to use. Non-parametric tests make fewer assumptions than parametric tests but can be less powerful.
Measurement levels
The document discusses the four levels of measurement: nominal, ordinal, interval, and ratio. Nominal measurement assigns values that name attributes uniquely without order. Ordinal assigns ordered but non-quantitative values. Interval assigns values where distances are meaningful. Ratio has all interval properties plus a true absolute zero, allowing meaningful ratios. The level of measurement impacts what statistical analyses can be done and how data should be interpreted.
IB ESS -How to write a Good Lab report
1) The document provides guidance for writing a good lab report for an Environmental Systems and Societies (ESS) Internal Assessment. It outlines the key sections that should be included in a planning lab report such as the aim, introduction, research question, hypothesis, variables, materials, procedure, references, and raw data.
2) It emphasizes defining a clear and focused problem by stating a specific research question and hypothesis. It also stresses the importance of properly controlling variables and describing how they will be controlled in the experiment.
3) Checklists are provided to help students ensure their planning lab report addresses defining the problem, selecting variables, and controlling variables appropriately. The document aims to guide students in writing a well-structured lab
Mba2216 week 11 data analysis part 03 appendix
Multivariate analysis involves simultaneously analyzing multiple variables to understand relationships. This document discusses key concepts in multivariate analysis including:
1. Defining multivariate analysis and when it is appropriate to use.
2. Describing specific techniques like multiple regression, discriminant analysis, logistic regression, MANOVA, canonical correlation analysis, conjoint analysis, factor analysis, cluster analysis, multidimensional scaling, and correspondence analysis.
3. Providing guidelines for selecting the appropriate technique based on the measurement scales and relationship between variables.
It also covers important considerations like measurement error, statistical power, and a structured approach to multivariate model building.
Basics of Educational Statistics (Variables and types)
Variables can take different values and include characteristics like height, weight, and age. There are two types of variables: quantitative and categorical.
Measurement scales define the structure and meaning of variables. The four types of measurement scales are nominal, ordinal, interval, and ratio. Nominal scales involve categories without ordering, like gender. Ordinal scales have ordered categories, such as rankings, but intervals between items are unknown. Interval scales have equal intervals but no true zero. Ratio scales are numbers with a true zero point.
The type of measurement scale affects the appropriate statistical analysis, so distinguishing between scales is important.
Chapter 6 data analysis iec11
This document outlines key concepts for analyzing qualitative and quantitative data. It discusses preparing data through editing, coding and inserting into a matrix. Graphical techniques like histograms, scatter plots and box plots are presented for depicting individual, comparative and relational data. Measures of central tendency, dispersion, relationships and models are explained including mean, median, standard deviation, correlation, and linear and non-linear models. The goal is for students to understand how to analyze data using appropriate statistical techniques and data visualization.
Correlational Study
There are three types of correlations: positive, negative, and no correlation. A positive correlation means that as one variable increases, the other also increases. A negative correlation means that as one variable increases, the other decreases. No correlation means the variables are unrelated and do not influence each other. While correlation does not prove causation, it can suggest relationships between variables and be used for prediction. Limitations of correlational research include the inability to determine cause and effect from the data.
Spss beginners
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
RSS 2012 Data Entry SPSS
SPSS can be used for data entry, cleaning, analysis, and presentation. It is important to prepare a data dictionary specifying variable names, codes, ranges, and missing values before entering data. Errors may occur during data collection or entry and can be detected using descriptive statistics, frequency distributions, logical checks, and double data entry. Suspicious values should be investigated rather than automatically changed to avoid correcting valid data.
Scale of measurement
There are four types of measurement scales: nominal, ordinal, interval, and ratio. Each scale allows for different types of statistical analysis. Nominal scales only allow categories to be grouped but no numerical differences. Ordinal scales maintain the order of categories but distances between categories are unknown. Interval scales have equal distances between categories and allow for addition and subtraction. Ratio scales have all the properties of interval scales plus a true zero point, allowing for multiplication and division.
KINLDE Advanced Statistics in Research Reading Understanding and Writing Up...
Advanced Statistics in Research is a non-technical introduction to complex multivariate statistics presented in research articles. It shows how to read, understand, and interpret sophisticated statistics like multiple regression, logistic regression, and ANOVA without showing how to perform the actual statistical procedures. The book explains key concepts like statistical significance, confidence intervals, and effect size. It also demonstrates how to summarize data analysis results in text, tables, and figures according to APA format.
How to Write a Lab Report
This document provides guidance on writing an effective lab report, including its typical structure and components. A lab report is a complete record of an experiment that includes enough detail for someone else to replicate the study. It generally consists of a cover page, introduction, statement of objective, materials and methods, results, discussion, references, and sometimes appendices. Each section has a specific purpose and content to include. The document emphasizes writing in past tense, avoiding interpretation in the results section, and providing thorough methodology to allow reproducibility.
SPSS-SYNTAX
This document provides an overview of a 2-day workshop on SPSS syntax that will be held on October 28th and 29th, 2010. The workshop will be organized by the Indian Institute of Psychometry in Kolkata and led by Dr. Debdulal Dutta Roy of the Psychology Research Unit at the Indian Statistical Institute in Kolkata. Topics that will be covered include an introduction to SPSS, its features and interfaces, how to write SPSS syntax for data management and analysis tasks, how to check data quality using syntax, and how to perform statistical analyses like correlations and descriptive statistics using syntax. Assignments involving practicing these skills with sample data will also be part of the workshop.
Abdm4064 week 11 data analysis
The document outlines 31 learning outcomes for data analysis. It discusses key concepts in data analysis including editing raw data, coding qualitative responses, constructing data files, and descriptive statistical analysis. The goal is for students to understand processes for preparing and summarizing data including editing, coding, and descriptive statistics.
Levels of measurement
This document discusses the four levels of measurement: nominal, ordinal, interval, and ratio. Nominal measurement involves categorizing variables qualitatively without numerical values. Ordinal measurement allows ranking variables but not determining degrees of difference. Interval measurement allows comparing differences but not ratios. Ratio measurement involves true quantities where ratios are meaningful and zero has a definite meaning. Knowing the level of measurement helps in interpreting and analyzing variable data appropriately.
Applied Statistical Methods - Question & Answer on SPSS
Applied Statistical Methods - Question & Answer on SPSS . This presentation from Erasmus at Portugal.
Statrting spss
This document provides an overview of starting SPSS, including installing the software, opening SPSS, the main SPSS windows, entering and saving data, and conducting statistical analysis. It discusses the SPSS data editor interface, defining variables, entering data by copying from Excel or directly into SPSS, and saving SPSS files. It also briefly mentions bibliographic citations for SPSS.
Planning the analysis and interpretation of resseaech data
The document outlines the researcher's plan for analyzing qualitative and quantitative data collected in a study. It discusses analyzing both types of data, including describing data, identifying typical and atypical findings, and answering research questions. Methods for analyzing qualitative data include historical analysis, inductive analysis, deductive analysis, and content analysis. Quantitative data analysis relies on statistical techniques to summarize data, identify similarities and differences between groups, and test hypotheses. Common statistical analyses include descriptive analysis, univariate analysis, bivariate analysis, multivariate analysis, and comparative analysis. The document also provides guidance on choosing appropriate statistical tests based on research questions, data type, and hypotheses.
Data measurement techniques
This document discusses scales of measurement in statistics. There are four main scales of measurement: nominal, ordinal, interval, and ratio. Each scale has certain properties that determine which statistical techniques can be appropriately used. The nominal scale involves categorical data and classification. The ordinal scale represents ordered relationships but there is no defined intervals between rankings. The interval scale allows comparisons of differences between values but not ratios, while the ratio scale includes all interval scale properties and has a true absolute zero value. Examples are provided for each type of measurement scale.
1 3 Variables and Types of Data
This document discusses different types of variables and levels of measurement. It defines qualitative and quantitative variables, as well as discrete and continuous variables. There are four levels of measurement for variables: nominal, ordinal, interval, and ratio. Nominal variables classify without order, ordinal can be ranked but differences are unknown, interval are ranked with precise differences but no true zero, and ratio have a true zero and allow for ratios. The document provides examples for each variable type and level of measurement.
Scale of Measurement
This document discusses different types of measurement scales used in qualitative and quantitative data analysis. A nominal scale assigns objects to discrete categories without numeric values. An ordinal scale ranks categories but the distances between ranks are unknown. An interval scale measures variables on a common scale at equal intervals and allows calculating means and medians, though ratios have no meaning. A ratio scale classifies, ranks, and compares intervals of objects, has a true zero point, and ratios between values are meaningful.
What's new in Rails 2?
An overview of the major new features and changes in Rails 2.0. Originally presented on December 11th, 2007 at NYC.rb.
PERIODISMO Y COMUNICACIÓN INSTITUCIONAL (clase 3)
El documento compara y contrasta el periodismo, las relaciones públicas, el marketing y la publicidad. Explica que el periodismo busca informar al lector para mejorar su vida, mientras que las relaciones públicas, el marketing y la publicidad buscan generar una imagen positiva o vender productos. También advierte sobre los peligros de una sociedad dominada por el consumo y las marcas, y propone la necesidad de un periodismo responsable, ético y comprometido con la verdad.
More Related Content
What's hot
Measurement levels
The document discusses the four levels of measurement: nominal, ordinal, interval, and ratio. Nominal measurement assigns values that name attributes uniquely without order. Ordinal assigns ordered but non-quantitative values. Interval assigns values where distances are meaningful. Ratio has all interval properties plus a true absolute zero, allowing meaningful ratios. The level of measurement impacts what statistical analyses can be done and how data should be interpreted.
IB ESS -How to write a Good Lab report
1) The document provides guidance for writing a good lab report for an Environmental Systems and Societies (ESS) Internal Assessment. It outlines the key sections that should be included in a planning lab report such as the aim, introduction, research question, hypothesis, variables, materials, procedure, references, and raw data.
2) It emphasizes defining a clear and focused problem by stating a specific research question and hypothesis. It also stresses the importance of properly controlling variables and describing how they will be controlled in the experiment.
3) Checklists are provided to help students ensure their planning lab report addresses defining the problem, selecting variables, and controlling variables appropriately. The document aims to guide students in writing a well-structured lab
Mba2216 week 11 data analysis part 03 appendix
Multivariate analysis involves simultaneously analyzing multiple variables to understand relationships. This document discusses key concepts in multivariate analysis including:
1. Defining multivariate analysis and when it is appropriate to use.
2. Describing specific techniques like multiple regression, discriminant analysis, logistic regression, MANOVA, canonical correlation analysis, conjoint analysis, factor analysis, cluster analysis, multidimensional scaling, and correspondence analysis.
3. Providing guidelines for selecting the appropriate technique based on the measurement scales and relationship between variables.
It also covers important considerations like measurement error, statistical power, and a structured approach to multivariate model building.
Basics of Educational Statistics (Variables and types)
Variables can take different values and include characteristics like height, weight, and age. There are two types of variables: quantitative and categorical.
Measurement scales define the structure and meaning of variables. The four types of measurement scales are nominal, ordinal, interval, and ratio. Nominal scales involve categories without ordering, like gender. Ordinal scales have ordered categories, such as rankings, but intervals between items are unknown. Interval scales have equal intervals but no true zero. Ratio scales are numbers with a true zero point.
The type of measurement scale affects the appropriate statistical analysis, so distinguishing between scales is important.
Chapter 6 data analysis iec11
This document outlines key concepts for analyzing qualitative and quantitative data. It discusses preparing data through editing, coding and inserting into a matrix. Graphical techniques like histograms, scatter plots and box plots are presented for depicting individual, comparative and relational data. Measures of central tendency, dispersion, relationships and models are explained including mean, median, standard deviation, correlation, and linear and non-linear models. The goal is for students to understand how to analyze data using appropriate statistical techniques and data visualization.
Correlational Study
There are three types of correlations: positive, negative, and no correlation. A positive correlation means that as one variable increases, the other also increases. A negative correlation means that as one variable increases, the other decreases. No correlation means the variables are unrelated and do not influence each other. While correlation does not prove causation, it can suggest relationships between variables and be used for prediction. Limitations of correlational research include the inability to determine cause and effect from the data.
Spss beginners
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
RSS 2012 Data Entry SPSS
SPSS can be used for data entry, cleaning, analysis, and presentation. It is important to prepare a data dictionary specifying variable names, codes, ranges, and missing values before entering data. Errors may occur during data collection or entry and can be detected using descriptive statistics, frequency distributions, logical checks, and double data entry. Suspicious values should be investigated rather than automatically changed to avoid correcting valid data.
Scale of measurement
There are four types of measurement scales: nominal, ordinal, interval, and ratio. Each scale allows for different types of statistical analysis. Nominal scales only allow categories to be grouped but no numerical differences. Ordinal scales maintain the order of categories but distances between categories are unknown. Interval scales have equal distances between categories and allow for addition and subtraction. Ratio scales have all the properties of interval scales plus a true zero point, allowing for multiplication and division.
KINLDE Advanced Statistics in Research Reading Understanding and Writing Up...
Advanced Statistics in Research is a non-technical introduction to complex multivariate statistics presented in research articles. It shows how to read, understand, and interpret sophisticated statistics like multiple regression, logistic regression, and ANOVA without showing how to perform the actual statistical procedures. The book explains key concepts like statistical significance, confidence intervals, and effect size. It also demonstrates how to summarize data analysis results in text, tables, and figures according to APA format.
How to Write a Lab Report
This document provides guidance on writing an effective lab report, including its typical structure and components. A lab report is a complete record of an experiment that includes enough detail for someone else to replicate the study. It generally consists of a cover page, introduction, statement of objective, materials and methods, results, discussion, references, and sometimes appendices. Each section has a specific purpose and content to include. The document emphasizes writing in past tense, avoiding interpretation in the results section, and providing thorough methodology to allow reproducibility.
SPSS-SYNTAX
This document provides an overview of a 2-day workshop on SPSS syntax that will be held on October 28th and 29th, 2010. The workshop will be organized by the Indian Institute of Psychometry in Kolkata and led by Dr. Debdulal Dutta Roy of the Psychology Research Unit at the Indian Statistical Institute in Kolkata. Topics that will be covered include an introduction to SPSS, its features and interfaces, how to write SPSS syntax for data management and analysis tasks, how to check data quality using syntax, and how to perform statistical analyses like correlations and descriptive statistics using syntax. Assignments involving practicing these skills with sample data will also be part of the workshop.
Abdm4064 week 11 data analysis
The document outlines 31 learning outcomes for data analysis. It discusses key concepts in data analysis including editing raw data, coding qualitative responses, constructing data files, and descriptive statistical analysis. The goal is for students to understand processes for preparing and summarizing data including editing, coding, and descriptive statistics.
Levels of measurement
This document discusses the four levels of measurement: nominal, ordinal, interval, and ratio. Nominal measurement involves categorizing variables qualitatively without numerical values. Ordinal measurement allows ranking variables but not determining degrees of difference. Interval measurement allows comparing differences but not ratios. Ratio measurement involves true quantities where ratios are meaningful and zero has a definite meaning. Knowing the level of measurement helps in interpreting and analyzing variable data appropriately.
Applied Statistical Methods - Question & Answer on SPSS
Applied Statistical Methods - Question & Answer on SPSS . This presentation from Erasmus at Portugal.
Statrting spss
This document provides an overview of starting SPSS, including installing the software, opening SPSS, the main SPSS windows, entering and saving data, and conducting statistical analysis. It discusses the SPSS data editor interface, defining variables, entering data by copying from Excel or directly into SPSS, and saving SPSS files. It also briefly mentions bibliographic citations for SPSS.
Planning the analysis and interpretation of resseaech data
The document outlines the researcher's plan for analyzing qualitative and quantitative data collected in a study. It discusses analyzing both types of data, including describing data, identifying typical and atypical findings, and answering research questions. Methods for analyzing qualitative data include historical analysis, inductive analysis, deductive analysis, and content analysis. Quantitative data analysis relies on statistical techniques to summarize data, identify similarities and differences between groups, and test hypotheses. Common statistical analyses include descriptive analysis, univariate analysis, bivariate analysis, multivariate analysis, and comparative analysis. The document also provides guidance on choosing appropriate statistical tests based on research questions, data type, and hypotheses.
Data measurement techniques
This document discusses scales of measurement in statistics. There are four main scales of measurement: nominal, ordinal, interval, and ratio. Each scale has certain properties that determine which statistical techniques can be appropriately used. The nominal scale involves categorical data and classification. The ordinal scale represents ordered relationships but there is no defined intervals between rankings. The interval scale allows comparisons of differences between values but not ratios, while the ratio scale includes all interval scale properties and has a true absolute zero value. Examples are provided for each type of measurement scale.
1 3 Variables and Types of Data
This document discusses different types of variables and levels of measurement. It defines qualitative and quantitative variables, as well as discrete and continuous variables. There are four levels of measurement for variables: nominal, ordinal, interval, and ratio. Nominal variables classify without order, ordinal can be ranked but differences are unknown, interval are ranked with precise differences but no true zero, and ratio have a true zero and allow for ratios. The document provides examples for each variable type and level of measurement.
Scale of Measurement
This document discusses different types of measurement scales used in qualitative and quantitative data analysis. A nominal scale assigns objects to discrete categories without numeric values. An ordinal scale ranks categories but the distances between ranks are unknown. An interval scale measures variables on a common scale at equal intervals and allows calculating means and medians, though ratios have no meaning. A ratio scale classifies, ranks, and compares intervals of objects, has a true zero point, and ratios between values are meaningful.
What's hot (20)
Basics of Educational Statistics (Variables and types)
Basics of Educational Statistics (Variables and types)
KINLDE Advanced Statistics in Research Reading Understanding and Writing Up...
KINLDE Advanced Statistics in Research Reading Understanding and Writing Up...
Applied Statistical Methods - Question & Answer on SPSS
Applied Statistical Methods - Question & Answer on SPSS
Planning the analysis and interpretation of resseaech data
Planning the analysis and interpretation of resseaech data
Viewers also liked
What's new in Rails 2?
An overview of the major new features and changes in Rails 2.0. Originally presented on December 11th, 2007 at NYC.rb.
PERIODISMO Y COMUNICACIÓN INSTITUCIONAL (clase 3)
El documento compara y contrasta el periodismo, las relaciones públicas, el marketing y la publicidad. Explica que el periodismo busca informar al lector para mejorar su vida, mientras que las relaciones públicas, el marketing y la publicidad buscan generar una imagen positiva o vender productos. También advierte sobre los peligros de una sociedad dominada por el consumo y las marcas, y propone la necesidad de un periodismo responsable, ético y comprometido con la verdad.
Cumple Monikita Y Tavito ûNov
El documento habla sobre un grupo de amigos que están cocinando y llenando una piñata para celebrar. Mientras algunos amigos están cocinando, otros están comiendo. Luego, cuando rompen la piñata, una amiga se queja de que no le dan dulces a pesar de que ella ayudó a traer la piñata.
Solving The Puzzles
The document provides three steps to solving puzzles: 1) Patience, 2) Logic, and 3) Faith. It defines each step, with patience being the first step to a solution. Logic is then defined as using reasoning to draw conclusions, referencing Sudoku rules. Faith is the final step, referencing biblical verses that define faith as having assurance of things unseen and having faith in God's promises.
Apartment Owners Forum
Dublin City Council held an open forum of discussion in the Atrium, Civic Offices, Wood Quay, Dublin 8 at 7.00pm on Tuesday October 30th 2007.
A panel of apartment owners, expert in many fields relevant to apartment owners (such as Auditing; Architecture; Fire Services; Corporate Governance; Law; Insurance; Property Valuation; Building Consultancy; Planning Enforcement; Debt Collection and Sinking Funds) presented and discussed matters concerning apartment living and membership of management companies.
Si Me Ves
El poema habla sobre levantarse cuando uno se siente cansado y derrotado en la vida. Alienta a no rendirse y a buscar el apoyo de amigos y familiares que puedan dar ánimo y motivar a seguir adelante. También enfatiza la importancia de mantener a los amigos que pueden ayudar a recordar el camino cuando más se les necesita.
Mastercard
Um touro de 503 kg foi leiloado por 9.000 euros. Entradas na primeira fila de uma tourada custaram 1.500 euros cada. Chapéus típicos da região foram vendidos por 530 euros. Uma cerveja custou 2 euros.
Marriage
According to Genesis 2:24, marriage involves three aspects: a man leaves his father and mother, he cleaves to his wife, and the two become one flesh through their union. The key verse discusses how a man shall leave his family to join with his wife, becoming a single unit or "one flesh".
Emitting Light
The document discusses two passages from the book of Matthew in the Bible. The first passage talks about recognizing false prophets by the fruit they bear and how good trees bear good fruit while bad trees bear bad fruit. The second passage discusses how followers of Christ are like a light that should shine for all to see, and that people will see their good works and glorify God as a result. The overall message is about bearing good fruit so that people recognize you as a follower of Christ, and being a light for others that leads them to glorify God.
conclusion
This document discusses how to write a conclusion for a geography paper. A conclusion should refer back to the original question or hypothesis, address each aim and prediction in turn based on the results, and provide an overall conclusion linked to the geographical theory, which may include an illustrative diagram.
VfI Briefing 5 Nov 2007
The document summarizes a presentation given at a Microsoft event in the UK. It discusses the state of the UK IT market, including key trends and economic impacts. It also covers emerging technologies, policy issues, and how attendees can get involved in influencing technology policy through an organization called Voices for Innovation.
PresentacióN Institucional
Este documento resume la creación de la Fundación Darsecuenta, una red de instituciones, empresas y personas en Argentina con el objetivo de promover un cambio de actitud en la población. Se detalla la constitución legal de la Fundación en 2007, sus áreas de trabajo, planes de comunicación y redes sociales, y las instituciones y empresas que la apoyan inicialmente.
Finding A Church
The document discusses finding a church off the FOB (forward operating base) and describes three characteristics of a good church:
1) A faithful church that holds firmly to God's word and does not deny His name.
2) A foundational church whose members persevere in keeping God's commands and will be kept from future trials.
3) A focused church that holds fast to what they have received from God and overcomes challenges so their crown cannot be taken.
Radiate Love
The document discusses the importance of loving God, our neighbors, and even our enemies. It cites several Bible passages that instruct believers to love God with all their heart, soul and mind. It also references passages about loving our neighbors as ourselves and doing good to those who hate us. The overall message is that we should radiate love to all people through obeying God's commandments to love Him and love others, even our enemies.
Doutro Lado
O documento descreve o planejamento de um projeto de estudantes sobre o envelhecimento na cidade de Amadora em Portugal. O grupo escolheu o tema, criou um blog e visitou um seminário. Eles planejam visitar instituições para idosos no segundo período para recolher informações e depois ajudar as instituições promovendo atividades, fazendo panfletos e trabalhando como voluntários.
Midansu Inteligencia
Este documento presenta una serie de ejercicios mentales breves como tests para evaluar la capacidad de cálculo mental y procesamiento rápido de información del cerebro. Los ejercicios incluyen sumas mentales, contar letras en un texto y responder preguntas mentales sobre herramientas y colores de forma rápida. Al final se indica que la mayoría de las personas piensan en un martillo rojo, lo que sugiere que son normales en su capacidad de pensamiento.
Giving
Jesus observed people donating money at the temple treasury, with many rich people donating large sums. A poor widow donated two small coins, which was all she had to live on. Jesus told his disciples that this widow had given more than the rich donors, because she had given out of her poverty while they gave out of their surplus.
Ejercicio
Este documento propone una sencilla rutina de ejercicios para el pie derecho que se puede hacer sentado en el escritorio para mantenerse en forma mientras se pasan horas frente al ordenador; consiste en levantar el pie derecho y hacer círculos hacia la derecha mientras se dibuja el número 6 en el aire con la mano derecha, lo que hace que el pie cambie automáticamente de dirección.
Standing In The Aisle
The document discusses building one's life and faith on a firm foundation through obedience to Jesus Christ's teachings. It explains that obedience is like building a house on rock, able to withstand storms, while disobedience is like building on sand and will result in collapse. To be obedient, one must read the Bible to understand God's word, and not just know it but do it, accepting Jesus as Lord and Savior to begin building a life on this solid foundation.
Viewers also liked (20)
Similar to analysis
Measurement and scaling techniques
This document discusses measurement and scaling techniques used in research. It begins by defining measurement and scaling, and describes four levels of measurement scales: nominal, ordinal, interval, and ratio scales. It then explains different scaling techniques, including comparative techniques like paired comparison scales and rank order scales, as well as non-comparative techniques like Likert scales. The document provides examples to illustrate each scaling technique and discusses how to select the appropriate technique for a given research problem.
Mk0013 marketing research
This document provides information about obtaining fully solved assignments. It lists an email address and phone number to contact for assignment help. It also includes 5 sample marketing research assignment questions with detailed multi-paragraph answers covering topics such as types of consumer and B2B market research, scales of measurement, sampling techniques, non-comparative scaling, and types of online marketing research. Students are encouraged to send their semester and specialization to the email or call the phone number provided to receive assistance with their assignments.
Mk0013 marketing research
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
(Prefer mailing. Call in emergency )
ch 13.pptx
The document discusses measurement and scaling techniques used in survey research. It defines measurement as observing and recording characteristics according to rules, while scaling assigns objects numbers or categories according to a rule. There are four levels of measurement scales: nominal for categories, ordinal for ranking, interval for equal distances, and ratio for a true zero. Comparative scales ask respondents to directly compare objects, while non-comparative scales evaluate objects independently. Common scaling techniques include Likert scales, semantic differential scales, and constant sum scales. The document aims to help select an appropriate attitude measurement scale for research.
Measurement and scaling techniques
This document discusses measurement and scaling techniques used in research. It defines measurement as observing and recording observations according to rules, while scaling is assigning objects to numbers or categories by rule. There are four levels of measurement: nominal, ordinal, interval, and ratio scales. Nominal scales use numbers as labels, ordinal scales show ranking, interval scales have equal distances between numbers, and ratio scales have a true zero point. Comparative scales like paired comparisons or ranking ask respondents to directly compare objects, while non-comparative scales like Likert or semantic differential scales rate single objects independently. The appropriate scale depends on the research problem and data type.
Measurement and scaling techniques
This document discusses measurement and scaling techniques used in research. It defines measurement as observing and recording observations according to rules, while scaling is assigning objects to numbers or semantics based on a rule. There are four levels of measurement scales: nominal, ordinal, interval, and ratio. Scaling techniques can be comparative, involving comparisons between objects, or non-comparative, involving single object evaluations. Common comparative techniques include paired comparisons, rank ordering, and constant sum, while common non-comparative techniques are continuous ratings and itemized ratings like Likert scales. The appropriate technique depends on the research problem and intended statistical analysis.
Chotu scaling techniques
The document discusses measurement and scaling techniques used in research. It begins by defining measurement and scaling, and describing four levels of measurement scales: nominal, ordinal, interval, and ratio scales. It then covers comparative scaling techniques like paired comparison scales and rank order scales, and non-comparative techniques like continuous rating scales and itemized rating scales, giving examples of Likert scales. The purpose is to explain how to select an appropriate attitude measurement scale for research problems.
Report writing.new
The document discusses the benefits of updating an industrial equipment company's operator interface technology from a hardwired system to a new touchscreen graphical display system. Research found the company's sales declined as competitors adopted the new technology. Cost analysis showed the new system would have similar installation costs but reduce wiring and I/O. Interviews with past customers and research showed the new system would improve usability and customer satisfaction. The report recommends adopting the new operator interface technology.
CHAPTER FOUR.pptx
The document discusses data analysis and the discussion of findings in research. It provides details on the differences between data analysis and discussion of findings. It explains that data analysis involves evaluating and analyzing collected data using logical reasoning to form findings or conclusions. It discusses important issues in data analysis like using sufficient datasets and samples and not delegating the analysis. It also discusses common components of qualitative data analysis such as data archiving, exploring cases, finding themes and categories. The discussion of findings section explains that this part involves interpreting results in relation to research questions and existing knowledge to demonstrate what is known, differences found, and how findings extend knowledge in the field.
Research Method chapter 6.pptx
This document provides an overview of qualitative data analysis. It discusses that qualitative data analysis involves coding, categorizing, comparing and interpreting collected data to find meanings and implications. The researcher's perspective influences the analysis. It also describes techniques for qualitative data analysis like becoming familiar with the data, providing in-depth descriptions, and categorizing data into themes. Ensuring credibility involves considering factors like the researcher's observations and biases. The document also contrasts qualitative data analysis with quantitative analysis.
Research Report (1).pptx
The document outlines the typical structure and components of a research report, including an introduction, methodology, findings, and conclusions. It also discusses various scaling techniques used in research such as paired comparison scales, rank order scales, constant sum scales, and Q-sort scales. Finally, it covers reference styles such as APA and MLA and defines plagiarism.
Week 4 data chart and bar graphs the data chart and bar gr
The document provides data from a summative assessment given to 15 learners in Week 3, including a data chart with each learner's score and two bar graphs showing questions answered incorrectly by learners and the number of incorrect answers. This data is to be analyzed for measures of central tendency, performance on the assessment, and how the results can inform future instruction and feedback.
Week 4 data chart and bar graphs the data chart and bar gr
The document provides data from a summative assessment given to 15 learners in Week 3, including a data chart with each learner's score and two bar graphs showing questions answered incorrectly by learners and the number of incorrect answers. This data is to be analyzed for measures of central tendency, performance on the assessment, and how the results can inform future instruction and feedback.
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.
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.
Scaling in research
This document discusses measurement and scaling techniques used in survey research. It defines measurement as observing and recording characteristics, while scaling involves assigning objects to numbers according to rules. There are four levels of measurement scales: nominal, ordinal, interval, and ratio. The document also describes and provides examples of comparative scales like paired comparison and rank ordering, as well as non-comparative scales like Likert scales and semantic differentials. The goal is to help researchers select the appropriate attitude measurement scale for their problem.
Survey report: Present the results with ready-made tables and charts
The way you analyze data matters, right?
With Startquestion ✅ you can easily create a valuable research report using ready-made charts and tables. With our tool you may:
1️⃣ Analyze trends
2️⃣ Summarize the results
3️⃣ Personalize reports
4️⃣ Compare large amounts of data
5️⃣ Drew advanced conclusions
6️⃣ Conduct sentiment analysis
And much more. Check it out!
See our blog posts to learn more about Startquestion features:
https://blog.startquestion.com/
t-Test Project Instructions and Rubric Project Overvi.docx
t-Test Project Instructions and Rubric
Project Overview
1. Choose a research question:
a) that can be addressed using a t-test
b) for which you can collect data to analyze
2. Devise a plan to collect your data
3. Submit a project plan form to the instructor and obtain approval
4. Once your research question and data collection plan are approved, carry out your research:
a) Collect data
b) Conduct t-test analysis, using guidelines below
c) Write your results in a report, using the outline given below
5. Turn in your written report using the link in Module 9 of the course Blackboard site.
Data Collection Options: The following are suggestions on where you can collect data.
1. Reliable/reputable websites (e.g., sponsored by the census bureau, professional sports leagues, universities, real estate
agencies, car manufacturers, consumer groups, financial institutions, well- known product manufacturers, restaurants/fast
food companies, weather tracking agencies, county/city/state/federal government organizations, etc.)
2. Visit to one or more locations where item(s) you are researching can be found (e.g., stores to write down prices, rivers
to count turtles, car dealers to write down data about cars, etc.)
3. Other resource by permission (if you have an idea, ask your instructor).
Important Note: ERAU and all other universities have strict policies and approval procedures for any research projects that involve
collecting data from human subjects. There is not time in this course for you to go through that approval process. Therefore, your
project in this course cannot involve directly collecting data from human subjects. This includes conducting surveys.
Project Design
There are 3 project design options for the t-test project, listed below. To see components and examples for each type of project
design, consult the t-test Project Examples Word document or the t-test Project Resources PowerPoint file.
A. The 1-sample t-test (Sample size must be at least n = 40.)
B. The matched pairs t-test (Sample size must be at least n = 40.)
C. The 2-sample t-test (independent samples) (Sample size must be at least n = 50. You may split this across your two
samples; for example, you may have two independent samples of size 25, or one of 27 and another of 23, etc. Although your
independent samples are not required to be identical in size, it is better if the sample sizes are similar.)
t-Test Project Instructions and Rubric Page 2 of 7
Revised 6/10/13
Project Plan Form
Download a copy of the project plan Word document, t-Test Project Plan, save a copy for your records, and then complete the form.
Upload the completed form using the link provided in the module assignment item. If the form is not completed satisfactorily, it will be
returned to you for revision.
NOTE:
Your project plan must be approved by the instructor before you may begin your ...
Scaling techniques
Measurement involves assigning numbers or symbols to object characteristics according to rules. Scaling creates a continuum to locate measured objects. There are several types of scaling techniques used in research. Nominal scaling uses numbers as labels for identification purposes only, while ordinal scaling ranks attributes in order. Interval and ratio scaling measure distances between attributes on a scale with consistent intervals or a true zero point.
Similar to analysis (20)
Week 4 data chart and bar graphs the data chart and bar gr
Week 4 data chart and bar graphs the data chart and bar gr
Week 4 data chart and bar graphs the data chart and bar gr
Week 4 data chart and bar graphs the data chart and bar gr
Survey report: Present the results with ready-made tables and charts
Survey report: Present the results with ready-made tables and charts
White and Beige Cute Illustrative Thesis Defense Presentation.pptx
White and Beige Cute Illustrative Thesis Defense Presentation.pptx
t-Test Project Instructions and Rubric Project Overvi.docx
t-Test Project Instructions and Rubric Project Overvi.docx
More from chrislivesey
All3cases
The document shows Latin noun declension charts comparing singular and plural nominative, accusative, and dative cases for the 1st, 2nd, and 3rd declension. Examples are given below the charts demonstrating how different nouns change form depending on their case, number, and gender when used in sentences.
Y9 options2012
The document provides information about course options for years 10 and 11 at a school. It lists the core subjects that all students must take, including English, maths, science, PE, citizenship and PRE. Students can then choose 4 additional subjects from a list of over 20 options across areas like arts, humanities, languages, sports studies and technology. The document includes examples of students selecting their preference subjects and fallback options based on their year 9 exam results in science.
Year 7 ila spring term 2 spellings
The document provides various spelling strategies for year 7 students, including:
1. Breaking words into sounds or syllables, looking at affixes or word origins, using mnemonics or words within words.
2. Applying common spelling rules such as doubling consonants after short vowels or with certain prefixes.
3. Guidelines for adding suffixes to words ending in silent e or -ce and -ge.
Y9 Options2010
This document provides information about course options and requirements for students in Key Stage 4 (years 10-11) at a school. It outlines the core subjects that all students must take, including English, maths, science, religious studies, citizenship, and PE. Students can then choose from over 20 additional GCSE subjects or vocational courses. The document provides details on subject areas and diploma options. It explains the process for students to indicate their preferred subjects and backup choices by a deadline to facilitate timetable planning.
Study Skills
The document provides eight methods for effective revision and memorization. It emphasizes that revision must occur often and be repeated at intervals for best recall. Some key methods include highlighting important points, making lists and mind maps to break content into chunks, learning diagrams and graphs thoroughly, grouping related concepts logically, using mnemonics, creating study cards, applying a seven-step process to read dense texts, and finding a study partner. Regular review spaced over time is crucial for long-term memory retention.
plurals
This document discusses Latin noun declensions and whether words should be in the singular or plural form. It lists Latin nouns that can be either singular or plural, such as agricola which can mean farmer or farmers, and urbes which can mean city or cities. The document examines the rules for determining if a Latin noun should be in the singular or plural form.
Globe
The document provides a quiz about terms related to Shakespearean theatre. It tests knowledge about groundlings (audience members who stood on the floor), playwrights (authors of plays), and puritans (strict protestants against theatres). It also defines key words like scripts (copies of plays with just lines), cutpurses (thieves who stole purses), and the plague (an infectious disease spread by rats). The quiz aims to teach readers unfamiliar Elizabethan theatre vocabulary.
Results
This document provides guidance on presenting results in an effective way for coursework. It recommends using visual presentations such as bar graphs, pie charts, line graphs, photos, maps, and star diagrams to display data in an easy to understand manner. The examiners will look for good presentation, appropriate and complex visualization techniques being used, and some incorporation of information and communication technology.
Methos
The document describes 6 different data collection techniques used to study housing and transportation in Harrow, England. It explains how each technique was conducted, why it was used, its limitations, and how the data was analyzed. The techniques included traffic counts, a land use survey, questionnaires, photos, and environmental assessments to understand housing preferences, land uses, traffic patterns, and more.
nameplate
This pupil chose some pictures for a school assignment, but it is unclear from the short document whether the chosen pictures were appropriate. The single sentence poses a question about the suitability of pictures selected by a pupil for a school project without providing any context or details about the pictures themselves.
More from chrislivesey (10)
Recently uploaded
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Securing your Kubernetes cluster_ a step-by-step guide to success !
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Essentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
20240605 QFM017 Machine Intelligence Reading List May 2024
Everything I found interesting about machines behaving intelligently during May 2024
UiPath Test Automation using UiPath Test Suite series, part 5
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Building RAG with self-deployed Milvus vector database and Snowpark Container...
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Recently uploaded (20)
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
analysis
- 1. Analysis The aim of this section is to analyse (make sense of ) the results and in doing so, relate them to your title and the objectives of your investigation in order to help you prove or disprove the original question or hypothesis.