This document provides an introduction to statistics, including definitions of key concepts. It explains that statistics involves collecting and analyzing data to answer questions and make decisions. It defines statistics as using a scientific process to extract information from data. It also outlines the differences between descriptive and inferential statistics, and defines important statistical terms like population, sample, parameter, and statistic. It describes the different types of data - nominal, ordinal, interval - and the appropriate calculations and variables for each. Finally, it distinguishes between discrete and continuous numerical data.
Assignment 2 RA Annotated BibliographyIn your final paper for .docxjosephinepaterson7611
Assignment 2: RA: Annotated Bibliography
In your final paper for this course, you will need to write a Methods section that is about 3–4 pages long where you will assess and evaluate the methods and analysis of your proposed research.
In preparation for this particular section, answer the following questions thoroughly and provide justification/support. The more complete and detailed your answers for these questions, the better prepared you are to successfully write your final paper:
· What is the problem being addressed by your research study?
· State the refined research question and hypothesis (null and alternative).
· What are your independent and dependent variables? What are their operational definitions?
· Who will be included in your sample (i.e., inclusion and exclusion characteristics)?
· How many participants will you have in your sample?
· How will you recruit your sample?
· Identify the type of measurement instrument to be used to collect the raw numeric data to be statistically analyzed and the type of measurement data the instrument produces.
· What issues will you cover in the informed consent?
· If there is potential risk or harm, how will you ensure the safety of all participants?
· Name any possible threats to validity and steps that can be taken to minimize these threats.
· What type of parametric or nonparametric inferential statistical process (correlation, difference, or effect) will you use in your proposed research? Why is this statistical test the best fit?
· State an acceptable behavioral research alpha level you would use to fail to accept or fail to reject the stated null hypothesis and explain your choice.
This paper may be written in question-and-answer format rather than a flowing paper. Write your response in a 3- to 4-page Microsoft Word document.
All written assignments and responses should follow APA rules for attributing sources.
Submission Details:
· By the due date assigned, save your document as M4_A2_Lastname_Firstname.doc and submit it to the Submissions Area .
Assignment 2 Grading Criteria
Maximum Points
Stated the problem being addressed.
8
Stated the refined research question and hypothesis (null and alternative).
6
Stated the independent and dependent variables and provided the operational definitions.
12
Discussed sample characteristics and size.
8
Discussed a sample recruitment strategy.
6
Identified the type of measurement instrument to be used and the type of measurement data the instrument produces.
8
Discussed the informed consent and potential risk and protection factors.
12
Named the possible threats to validity and steps that can be taken to minimize these threats.
12
Discussed the type of parametric or nonparametric inferential statistical process that will be used and why it is a best fit.
8
Stated an acceptable behavioral research alpha level for analyzing the data.
4
Wrote in a clear, concise, and organized manner; demonstrated ethical scholarship in accurate representation and attrib.
Assignment 2 RA Annotated BibliographyIn your final paper for .docxjosephinepaterson7611
Assignment 2: RA: Annotated Bibliography
In your final paper for this course, you will need to write a Methods section that is about 3–4 pages long where you will assess and evaluate the methods and analysis of your proposed research.
In preparation for this particular section, answer the following questions thoroughly and provide justification/support. The more complete and detailed your answers for these questions, the better prepared you are to successfully write your final paper:
· What is the problem being addressed by your research study?
· State the refined research question and hypothesis (null and alternative).
· What are your independent and dependent variables? What are their operational definitions?
· Who will be included in your sample (i.e., inclusion and exclusion characteristics)?
· How many participants will you have in your sample?
· How will you recruit your sample?
· Identify the type of measurement instrument to be used to collect the raw numeric data to be statistically analyzed and the type of measurement data the instrument produces.
· What issues will you cover in the informed consent?
· If there is potential risk or harm, how will you ensure the safety of all participants?
· Name any possible threats to validity and steps that can be taken to minimize these threats.
· What type of parametric or nonparametric inferential statistical process (correlation, difference, or effect) will you use in your proposed research? Why is this statistical test the best fit?
· State an acceptable behavioral research alpha level you would use to fail to accept or fail to reject the stated null hypothesis and explain your choice.
This paper may be written in question-and-answer format rather than a flowing paper. Write your response in a 3- to 4-page Microsoft Word document.
All written assignments and responses should follow APA rules for attributing sources.
Submission Details:
· By the due date assigned, save your document as M4_A2_Lastname_Firstname.doc and submit it to the Submissions Area .
Assignment 2 Grading Criteria
Maximum Points
Stated the problem being addressed.
8
Stated the refined research question and hypothesis (null and alternative).
6
Stated the independent and dependent variables and provided the operational definitions.
12
Discussed sample characteristics and size.
8
Discussed a sample recruitment strategy.
6
Identified the type of measurement instrument to be used and the type of measurement data the instrument produces.
8
Discussed the informed consent and potential risk and protection factors.
12
Named the possible threats to validity and steps that can be taken to minimize these threats.
12
Discussed the type of parametric or nonparametric inferential statistical process that will be used and why it is a best fit.
8
Stated an acceptable behavioral research alpha level for analyzing the data.
4
Wrote in a clear, concise, and organized manner; demonstrated ethical scholarship in accurate representation and attrib.
Data Presentation & Analysis Meaning, Stages of data analysis, Quantitative & Qualitative data analysis methods, Descriptive & inferential methods of data analysis
Statistics is the scientific and mathematical analysis that uses quantified models, representations, etc. for collecting, interpreting, analysing and presenting empirical data. The presentation focuses on the significance of statistics, statistics as a career choice, varied career paths in statistics, various data types in statistics, etc.
Types of Data, Difference between Primary and Secondary Data, Collection of Primary Data, Questionnaire, Schedules, Interview, Survey, Observation, Secondary Data, Sources of Secondary Data, Tabulation of Data – Meaning and Types
Introduction to Statistics -
Sampling Techniques, Types of Statistics, Descriptive Statistics,
Inferential Statistics,
Variables and Types of Data: Qualitative, Quantitative, Discrete,
Continuous, Organizing and Graphing Data: Qualitative Data, Quantitative Data
Data Presentation & Analysis Meaning, Stages of data analysis, Quantitative & Qualitative data analysis methods, Descriptive & inferential methods of data analysis
Statistics is the scientific and mathematical analysis that uses quantified models, representations, etc. for collecting, interpreting, analysing and presenting empirical data. The presentation focuses on the significance of statistics, statistics as a career choice, varied career paths in statistics, various data types in statistics, etc.
Types of Data, Difference between Primary and Secondary Data, Collection of Primary Data, Questionnaire, Schedules, Interview, Survey, Observation, Secondary Data, Sources of Secondary Data, Tabulation of Data – Meaning and Types
Introduction to Statistics -
Sampling Techniques, Types of Statistics, Descriptive Statistics,
Inferential Statistics,
Variables and Types of Data: Qualitative, Quantitative, Discrete,
Continuous, Organizing and Graphing Data: Qualitative Data, Quantitative Data
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
2. Preface
What is Statistics?
Statistics is not just about analyzing the data.
It’s about the whole process of using the
scientific method to answer questions and make
decisions. That process involves
designing studies, collecting good data,
describing the data with numbers and graphs,
analyzing the data, and then making
conclusions.
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3. What is Statistics?
Statistics is a way to get information from data
data”
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Data
Statistics
Information
Data: Facts, especially
numerical facts, collected
together for reference or
information.
Information: Knowledge
communicated concerning
some particular fact.
Statistics is a tool for creating new understanding from a set of numbers.
4. Why do you analyse data?
1- To choose the correct statistical technique.
2- to compute the statistics.
3- to interpret the statistical results.
Stage 2 can be done manually to help students to
understand techniques and concepts, or using Excel,
Minitab, or SPSS.
Stage 1&3 provide students with practical skills to
apply to real problems.
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5. • Selecting the right technique depends on the
problem objective & data type.
• We are going to focus on how the techniques
and concepts introduced are applied to real-
world problems.
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6. Descriptive Statistics
It deals with methods of organizing,
summarizing, and presenting data in a
convenient and informative way, using
graphical techniques that make it easy to
extract useful information, or numerical
techniques to summarize data.
Selecting the appropriate technique depends on what
specific information we would like to extract.
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7. Inferential Statistics
It is a body of methods used to draw conclusions
or inferences about characteristics of
populations based on sample data.
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8. Key Statistical Concepts…
•
Population
— A population is the group of all items of interest
to a statistics practitioner.
— frequently very large; sometimes infinite.
E.g. All 5 million Florida voters can vote on election day
_ A descriptive measure of a population is called a
parameter.
_ In most applications, the parameter represents
the information we need.
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9. •
Sample
— A sample is a set of data drawn from the population.
— Potentially very large, but less than the population.
E.g. a sample of 765 voters who exit the polling
booth on an election day.
_ A descriptive measure of a sample is called a statistic.
_ We use statistics to make inferences about
parameters.
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11. Statistical Inference…
Statistical inference is the process of making an
estimate, prediction, or decision about a population
based on a sample data.
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Parameter
Sample
Statistic
Inference
What can we infer about a Population’s Parameters
based on a Sample’s Statistics?
12. • This can be done with a measure of reliability
called the confidence level, which is the
proportion of times that an estimating
procedure will be correct.
• Or the significance level, which measures how
frequently the conclusion will be wrong in the
long run.
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13. Types of Data and Information
• A variable is some characteristic of a
population or a sample.
• The values of the variable are the possible
observations of the variable.
• Data are the observed values of a variable.
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15. Types of Data and Information
Nominal Data ( also called categorical or
qualitative)
Such as marital status, gender,......
We often record nominal data by arbitrarily
assigning a number to each category (codes)
to store this type of data.
Male 1
Female 2
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16. Interval data ( quantitative or numerical)
Are real numbers, such as weights, heights, and
incomes.
Ordinal Data appear to be nominal, but their numerical
codes are in order.
Because the codes are arbitrarily assigned, we cannot
calculate and interpret the differences.
When assigning codes to the values, we can use any set
of codes , but we should maintain the order of the
values.
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17. Examples of Ordinal data
• Degree of illness: none, mild, moderate, acute,
chronic.
• Opinion of students about Stat. classes:
Very unhappy, unhappy, neutral, happy, Very happy.
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18. Calculations for Types of Data
Interval Data :values are real numbers, all
calculations are valid.
Ordinal data : The only permissible calculations
are ones involving the ranking process .
Nominal Data : values are the arbitrary numbers
that represent categories to be used to store
data. Only calculations based on the
frequencies of occurrence are valid( to count
the occurrence of each category).
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19. Hierarchy of Data
• The data types can be placed in order of the
permissible calculations. Higher-level data
may be treated as lower-level ones, but not
the vice versa.
Interval data
Ordinal data
Nominal data
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20. Types of Variables
• The variables whose observations
constitute our data will be given the
same name as the type of data.
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