Category: Statistics Homework Help

Control systems and data acquisition are important components of critical infrastructure and industrial processes. Control systems, such as Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and Industrial Control Systems (ICS), are used to monitor, control, and automate various operations in sectors like energy, water, manufacturing, and transportation. Data acquisition involves collecting and analyzing data from sensors, instruments, and other sources to gain insights and make informed decisions. Here are the importance of control systems and data acquisition, along with issues related to securing data and systems:

Importance of Control Systems and Data Acquisition:

1. Operational Efficiency: Control systems enable organizations to improve efficiency by automating processes, reducing manual intervention, and optimizing resource utilization. Data acquisition helps monitor key parameters and collect real-time data for analysis, allowing organizations to identify areas for improvement and make data-driven decisions.
2. Safety and Reliability: Control systems ensure safety and reliability in critical infrastructure operations. They enable real-time monitoring of equipment and processes, detection of anomalies or failures, and prompt response to mitigate potential risks. Data acquisition provides valuable insights into system performance, enabling proactive maintenance and enhancing safety measures.
3. Process Optimization: Control systems and data acquisition help optimise processes and workflows. By continuously monitoring and analyzing data, organizations can identify bottlenecks, optimize resource allocation, and streamline operations for increased productivity and cost-effectiveness.
4. Decision-Making and Planning: Control systems and data acquisition provide organizations with information for informed decision-making and strategic planning. Real-time data and historical trends help in forecasting, capacity planning, and resource allocation, ensuring efficient utilization of resources and effective long-term planning.

Issues with Securing Data and Systems:

1. Cybersecurity Threats: Control and data acquisition systems are vulnerable to cybersecurity threats. Malicious actors may target these systems to disrupt operations, steal sensitive information, or cause physical damage. Cybersecurity measures, such as network segmentation, access controls, encryption, and intrusion detection systems, are essential to protect control systems and data.
2. Legacy Systems and Integration Challenges: Many control and data acquisition systems in critical infrastructure sectors were developed before the proliferation of connected devices and modern cybersecurity standards. Legacy systems often lack adequate security measures, and integrating them with newer technologies can be challenging, creating potential vulnerabilities.
3. Insider Threats: Insider threats, intentional or unintentional, pose a risk to the security of control systems and data acquisition. Employees or authorized personnel with privileged access can inadvertently or maliciously compromise system integrity or data confidentiality. Strong access controls, employee training, and monitoring mechanisms are essential to mitigate insider threats.
4. Supply Chain Risks: Control and data acquisition systems rely on a complex supply chain involving multiple vendors and third-party components. Vulnerabilities in the supply chain, such as compromised hardware or software, can introduce security risks. Organizations must carefully assess and manage supply chain risks through vendor evaluations, secure development practices, and regular updates and patches.
5. Lack of Awareness and Training: Insufficient awareness and training among personnel can lead to unintentional security lapses. Employees may fall victim to phishing attacks, use weak passwords, or inadvertently disclose sensitive information. Organizations must invest in cybersecurity awareness programs and regularly train employees to promote a security-conscious culture.
6. Patch Management: Control and data acquisition systems often require frequent updates and patches to address vulnerabilities and security flaws. However, implementing these updates can be challenging due to concerns about system downtime, compatibility issues, or limited testing capabilities. Organizations need effective patch management strategies to balance security needs with operational continuity.

Securing control systems and data acquisition requires a multi-layered approach, including robust cybersecurity practices, regular risk assessments, employee awareness, secure development practices, and collaboration with industry peers and government entities. It is essential to stay vigilant, adapt to evolving threats, and prioritize critical infrastructure security and sensitive data.

Data Exploration, Visualization, and Pre-Processing Guidelines and Rubric

Prompt:

This milestone aims to clearly understand the details of the data set you choose since you will be working with this data set. Throughout the course and analyzing it for your final project. Specifically, you will inspect, clean, visualize, and transform the data in this milestone.

Assignment. As you work through the steps below, you will document your process and include them in your written submission.

Data Exploration, Visualization, and Pre-Processing Guidelines

Tech Sales Rep Data

Next, download your dataset and follow the steps below to inspect, clean, visualize, and transform the data. To complete your milestone assignment, you will create a report in a Microsoft Word document that addresses the specific prompts in each step.

Step 1: Determine Missing Values (If Any)

Begin by determining how many missing values each variable has. Be sure to address the following in a Microsoft Word document for your

Milestone 1 submission:

• Identify the missing values (Note: If you are using the College Admission dataset, you need first transfer the College_GPA column to a column

● Explain which strategy you used to handle the missing values (omission or imputation) and why you chose this method

● After you handle missing values, use the new data sets for further analysis

Step 2: Identify Potential Outliers

Use the interquartile method to detect potential outliers in any predictor variables. Depending on which dataset you selected, the following variables to determine whether there are outliers or not:

· If you are using Tech Sales Rep Data, use Salary and Years

Once you detect potential outliers in any of the predictor variables, be sure to address the following in your Milestone 1 submission:

● Identify any potential outliers

● Explain how you handle outliers in your dataset

Step 3: Subset the Dataset Based on Variables

In this step, you will subset your data. Note that nothing needs to be submitted for this step, but you will not be able to complete Step 4 until

you’ve completed the actions in Step 3.

To complete this step, you must subset your dataset based on the following:

If you are using Tech Sales Rep Data, subset the data based on business.

Step 4: Compare Summary Statistics of Subsets

Next, you will organize the data subsets you created in Step 3 in a table that shows the summary statistics. Use simple summary measures such.

as mean, median, minimum, maximum, and standard deviation in the subsets, and compare the summary statistics of your subsets to determine. Whether any differences exist across subsets.

Based on the dataset you have selected, use the following variables to compare the summary statistics of your subsets:

· Tech Sales Rep Data: Feedback, Salary, and NPS scores

Once you have completed your comparison, be sure to summarize your findings in a way that a non-technical person can understand in your

Milestone 1 submission. Specifically, be sure to address the following:

● Create a table that shows your summary statistics

● Compare the summary statistics of your subsets

● Determine whether any differences exist across subsets

Step 5: Create a Visualization of the Data

For this step, you will create a data visualization by following the instructions below, and addressing the relevant questions in your written.

milestone report. In your visual, axes should be clearly marked with the numbers of respective scales; each axis should be labeled. Be sure to

summarize your findings in the written report in a way that a non-technical person could understand.

Depending on the dataset you selected, follow the instructions below to construct a scatter plot:

1. Tech Sales Rep Data

A. Construct a scatter plot that shows the salary on the y-axis and experience on the x-axis.

B. Use different colors to show whether the business is in the hardware or software industry.

c. Describe the relation between salary and years of experience.

D. Explain whether this relationship holds for both hardware and software industries.

6. Save the Cleaned Dataset and Finalize Your Written Report

6. To complete this milestone, save your clean copy of the data set and finalize your milestone written report. Your report must be written in

essay format (with an introduction, body, and conclusion), and summarize your findings in a way that a non-technical person can understand.

You can find examples of a well-written report in your textbook in the “Writing with Big Data” section at the end of each chapter. The content of

your written report will be assessed based on the following criteria:

● Your written report must be well-presented and argued.

● Your ideas should be detailed, developed, and supported with evidence, data analysis, tables, and figures as appropriate.

● A non-technical audience must be able to easily understand the content.

Submission Guidelines: Your final submission must be submitted as a 2- to 3-page Microsoft Word document with double spacing, 12-point.

Times New Roman font, 1-inch margins, and should include a table that shows the summary statistics for Step 4.

MGT1005 Research Methods and Statistics Project: Conducting Primary Research

Project Assignment — is due on ___________ . Late submissions are subject to the maximum grade of a “C” and possibly other penalties.

Directions to Students: You have explored a scenario that posed a problem in at least one of your management courses (MGT1000 Values and Ethics in the Business Environment or MGT1003 Supervisory Management). In this project, you will conduct primary research to support or refute evidence you found while exploring the issues surrounding your scenario. No other coursework may be used for this project. You will now apply the processes of conducting primary research that you have learned in this class. Your investigation should follow the format that is outlined below. Before starting this project, your instructor must review your work from the written project in MGT1000 or MGT1003. You should provide your instructor with a folder containing the following documents during the second week of class: 1. A copy of the scoring rubric from your MGT100/MGT1003 project; 2. Your revised MGT1000/MGT1003 project is based on the scoring rubric. 3. Your original BBA Tracking Sheet signed by your MGT1000/MGT1003 instructor. 4. A copy of your scenario from MGT1000/MGT1003. Please keep a copy of all documents submitted to your instructor. Also, you should ensure you keep all of your drafts and research from your MGT1000/MGT1003 in a safe place, as you will need this in MGT1006. Please take a moment to review the scoring rubric for this project to ensure you understand the criteria for how your project will be graded.

Research Methods and Statistics Project: Conducting Primary Research

Research Project Assignment Receiving F Grade

A rubric will score Your Research Project Assignment. If your Research Project Assignment does not receive a passing score, you will receive a failing grade for the class. However, your instructor may recommend you for intersession assistance if he/she determines that you have grasped the essential concepts of the course, as demonstrated by adequate progress in other assessments performed in the course. The cost of this intersession assistance is $135 for two tutoring sessions. To qualify for this assistance, you must sign a contract explaining the requirements in detail, along with a submittal date before the beginning of the following term. The maximum grade you can receive if you go through the tutoring sessions and submit a passing project is a “C” grade. A Failing Research Project Assignment that has been revised will not be accepted unless the student has demonstrated fulfillment of the contract.

Part I: The Issue: You must have the following information in this section:

1. In your own words, summarize the scenario and identify the problems within the scenario. Provide some background information.

2. Justify why it is important for managers and supervisors to be knowledgeable about and the consequences of failing to handle the issue timely and appropriately.

3. Restate your conclusion from your secondary research.

Part II: Research Purpose: What is the purpose of the research you will be conducting? Are you further exploring evidence you found from conducting your secondary research? Are you discovering information about what other groups think concerning your project? Are you hoping to support the information that you found? Research can be done for a variety of reasons and purposes. Use creativity in thinking about supporting or refuting your secondary research.

Part III: Hypothesis and Survey Design: State your hypothesis. What do you think you will find as the result of your research?

Design your research experiment: From understanding how to conduct research select one or more methods. In this project, you must develop a survey, but you can also select and use additional research methods. Identify the population you selected for research and the specific characteristics of this population. Explain in detail the process of creating your survey – For example: how was your sample frame selected, what did you have to do to create the online survey, explain how you collected and organized your data, what types of questions did you use, what are the advantages/disadvantages of the question type you chose, etc. You must use all the required statistical terminologies outlined in the Additional Required Information section below. See the Survey Design section below for help with composing your survey questions.

Part IV: Summary of Data — Charts and Graphs: Summarize your data in charts and graphs for each survey question. Describe your findings using statistical methods such as frequency distributions, mean, median, mode, and standard deviation, and identify four links between collected data. You must calculate the mean, median, mode, standard deviation, and five-number summary for at least one question. The calculations and formulas must be attached to your report and referred to in your paper as Exhibit A. Reminder: To use the mean and standard deviation, your response categories must be numerical, not categorical. To fulfill this requirement, a good question is “What is your age?” You must use all the required statistical terminologies outlined in the Additional Required Information section below.

Interpret your data: What do the measures indicate? What did you learn from the data? Were there any trends or relationships you observed? For example: Analyze your population’s demographic characteristics. Your discussion should explain whether or not your population is accurately represented in your data. Show how your standard deviation, five-number summary, mean, and median calculations apply to the age demographic. Hint: Apply the 68—95—99.7 Rule (Chapter 13 in your textbook) for normal distributions to your data.

Part V: Conclusion: Summarize what you have found; does the information you collected support what you expected to find? How did you consider the opinion of others? Does your hypothesis support or refute your point of view? Do you think your findings are accurate, or could there be bias involved or other problems that could influence the data’s accuracy and reliability? For example, in reviewing your survey, were your response variables to questions designed thoroughly enough to cover a broad range of potential preferences of individuals?

REMAINDER OF PAGE LEFT BLANK

Survey Design

General Information:

1. Your survey must contain a minimum of five (5) demographic questions and five (5) categorical questions (scenario/topic-related questions).

2. There must be a minimum of four (4) possible responses for each multiple-choice question. If you use “All of the above” or “None of the above,” you must have four (4) other responses for your participants to choose from. You are limited to one (1) yes/no response question OR one (1) true/false question.

3. If you use an online survey website to create questions where the respondent can choose multiple-response answers, you must ensure that your question allows for this. You should also ensure that ALL of your survey questions are required to be answered.

4. You must proofread your survey to ensure that your introduction, questions, and response variables are grammatically correct and have no spelling, capitalization, or punctuation errors.

Survey Questions:

1. You need to be creative in developing your survey questions to ensure that they are designed to give you data to help support your hypothesis.

2. Make sure your survey questions match your research objectives. When developing your questions, ask yourself these two questions: How does this question relate to my scenario? How does this question relate to my decision in my secondary research project?

3. Try to develop an ability to think like your potential respondents. If you can effectively consider how your research participants will interpret and react to each question on your survey, then your resulting data will likely provide useful information.

4. Use language that is understandable to the type of respondents you are targeting. Consider the age of your respondents, their educational level, and any other relevant cultural characteristics of your respondents when deciding how to phrase your questions.

5. Avoid biased questions. This type of question may contain biased terminology or are worded so that they are slanted to a particular answer. Your questions should be neutral so that the respondent can think their own thoughts about the question.

6. Feel free to use open-ended questions (a person can answer any way they want). Remember that this type of question can be hard and time-consuming to analyze. However, you may get some good ideas from the responses that can help make your project more interesting.

7. Organize your survey questions in a logical sequence. For example, put all of your demographic questions first; then, put your topic questions in order from a general topic question to a more specific topic question sequence.

Survey Question Answers:

1. Make sure you have the most common answers available.

2. Try to avoid neutral answers (such as “don’t care” or “don’t know”) because people may choose them so they don’t have to think about the answer.

3. Having an “other” category can be helpful if none of the choices are satisfactory for the person answering the question.

4. Make sure each question is set up so you can present the answers how you want. Example: Having 5-6 response categories makes a nice display for a bar graph or pie chart; having more than six can make unsightly, confusing graphs, especially pie charts.

Survey Responses:

1. You must have a minimum of twenty-five (25) responses to your survey.

2. You must prepare a graph exhibiting the results for each question in your survey.

Additional Required Information

Your project MUST contain the following statistical terminology:

Short Answer Assignment #4

Part 1

PURPOSE: This assignment aims to help you better understand graphical depictions of factorial designs, including main and interaction effects.

TASK: Read the following information and prompts, and use your textbook and class notes to answer the following questions.

CRITERIA: You will be successful on this assignment if you can: (a) Provide a correct answer to all of the questions using course concepts and descriptions that are clear to another reader.

INFORMATION:

Scientists test whether the Independent Variable influences the dependent variable.

Scientists test whether the Dependent Variable depends on the independent variable.

When an experiment has TWO independent variables, the results are broken down:

• Main effect of independent variable #1 on the dependent variable
• Main effect of independent variable #2 on the dependent variable
• Interaction effect of the independent variables on the dependent variable
• The results are often summarized graphically when experiments test the effects of two independent variables on a dependent variable. In this homework assignment, you will be asked to interpret graphical results of experiments with two independent variables.

Quick guide for getting correct answers on this assignment:

• x-axis = the independent variable
• y-axis = dependent variable #1 (“IV #1”)
• Key (upper-right) = independent variable #2 (“IV #2”)
• Is there a main effect of IV #1?
  • If the average slope of the two lines…
    • … is Flat à no main effect of IV #1
      • e.g., both are flat, or if they cancel each other out by making an “X”
    • … both slope upward or downward = main effect of IV #1
• Is there a main effect of IV #2?
  • If the midpoint of the two lines is equal height à no main effect of IV #2
  • If the midpoint of one of the lines is higher/lower than the other à there is a main effect of IV #2
• Is there an interaction effect?
  • If the lines are parallel, there is NO interaction effect.
  • If the lines are NOT parallel, there is an interaction effect.
• Note: The graphs below represent fabricated data. It’s all made up, just for interpretation practice.

ASSIGNMENT:

For each graph, answer the questions. Explain all effects.

Example:

1. Graph 1
   1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

• Graph 2

1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

• Graph 3

1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

• Graph 4

1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

• Graph 5

1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

• Graph 6

1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

• Graph 7

1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

• Graph 8

1. Dependent Variable:

• Independent Variable 1:

• Independent Variable 2:

• Main effect of IV1:

• Main effect of IV2:

• Interaction Effect:

Part 2

PURPOSE: The purpose of this assignment is to help you practice designing a research study and gain a better understanding of small-N research designs.

TASK: Read the prompts below and answer the following questions that will help you design a series of small-N studies.

CRITERIA: You will be successful on this assignment if you can: (a) Provide a correct answer to all of the questions using course concepts and descriptions that are clear to another reader.

ASSIGNMENT:

Read the prompts and answer the questions:

1. Imagine you live in a dormitory with a roommate. This roommate is particularly messy, and you would like to change a behavior of theirs to improve the cleanliness of your shared room.
   1. Pick a behavior you think would improve the cleanliness of your shared dorm.

• What is an intervention you will use to change your roommate’s behavior?

• Use a stable-baseline design to test your intervention and sketch a graph to show what it would look like if the intervention worked.

• A teacher wants to show that attending after school tutoring improves students quiz grades over the course of a semester.
  • Design a multiple-baseline study to support her view.

• Sketch a graph or graphs to show what it would look like if the teacher was right.

• A researcher thinks that starting your day by journaling improves your daily mood.
  • Design a reversal study to test the researchers’ hypothesis.

• Sketch a graph to show what it would look like if the researcher was correct.

Part 3

PURPOSE: The purpose of this assignment is to help you practice your research skills while building your understanding pf Psychology’s Replication Crisis.

TASK: Using the UTA library or Google Scholar, find the journal article below. Once you have read the article and have a good understanding of the study, answer the following questions.

CRITERIA: You will be successful on this assignment if you can: (a) Provide a correct answer to all of the questions using course concepts and descriptions that are clear to another reader, (b) demonstrate you have read the article by citing specific facts and information from the article.

ASSIGNMENT:

Using the UTA library or Google Scholar, find the article titled “Psychology, Science, and Knowledge Construction: Broadening Perspectives from the Replication Crisis” and read the first 7 pages up through the sub-heading “Statistical Responses…” Then, answer the questions below.

1. How would you summarize psychology’s replication crisis? What is it?

• According to Shrout and Rodgers (2018), what are the major factors that have contributed to the crisis?

• What steps have been taken to address the crisis? Knowing what we know now, how can researchers be proactive about NOT making the crisis worse?

• Can you think of any other steps that can be taken to address the crisis?

• What other thoughts do you have about this issue?

Complete a data analysis report using ANOVA for assigned variables.

Introduction

You’re starting to learn some important information about your data, but you still want to know more. It’s time for a one-way analysis of variance (ANOVA). Unlike t-tests, which only allow for comparisons of two groups, ANOVA will allow you to examine potential group differences for variables with multiple levels.

Instructions

For this assessment:

• Use the Data Analysis and Application template (DAA Template [DOCX]).
• For help with the statistical software, refer to the JASP Step-by-Step: ANOVA [PDF] document.
• View JASP Speedrun: ANOVA [Video] for a brief tutorial video on this assessment.
• Refer to the 7864 Course Study Guide [PDF] for information on analyses and interpretation.
• For information on the data set, refer to the 7864 Data Set Instructions [PDF] document.

The grades.jasp file is a sample data set. The data represent a teacher’s recording of student demographics and performance on quizzes and a final exam across three sections of the course. 

This assessment is on ANOVA. You will analyze the following variables in the grades.jasp data set:

Variables and Definitions

Step 1: Write Section 1 of the DAA: Data Analysis Plan

• Name the variables used in this analysis and whether they are categorical or continuous.
• State a research question, null hypothesis, and alternate hypothesis for the ANOVA.

Step 2: Write Section 2 of the DAA: Testing Assumptions

Test for one of the assumptions of ANOVA – homogeneity.

• Create statistical software output showing the Levene’s Test for Equality of Variances.
• Paste the table in the DAA template.
• Interpret the homogeneity test to determine whether the assumption of homogeneity is violated or is not violated.

Step 3: Write Section 3 of the DAA: Results & Interpretation

• If the homogeneity assumption is not violated (Section 2), run the “Homogeneity corrections: None” version of the ANOVA. Follow up with the “Standard” version of the Tukey post hoc test.
• However, if the homogeneity assumption is violated (Section 2), run the “Homogeneity corrections: Welch” version of the ANOVA. Follow up with the “Games-Howell” version of the Tukey post hoc test.

Paste the following statistical software tables into the document:

• Descriptives table.
• ANOVA table.
• Post Hoc Tests table (Tukey correction).

Below the output:

• Report the means and standard deviations of quiz3 for each group of the section variable.
• Report the results of the F test and interpret the statistical results against the null hypothesis; state whether the null hypothesis is rejected or not rejected. 
• Finally, if the F is significant, interpret the post-hoc tests.

Step 4: Write Section 4 of the DAA: Statistical Conclusions

• Provide a brief summary of your analysis and the conclusions drawn about this ANOVA.
• Analyze the limitations of the statistical test and/or possible alternative explanations for your results.

Step 5: Write Section 5 of the DAA: Application

• Name an independent variable (the IV should have three or more groups or categories) and dependent variable that would work for such an analysis and why studying it may be important to the field or practice.

Submit your DAA Template as an attached Word document in the assessment area.

Software

The following statistical analysis software is required to complete your assessments in this course:

• Jeffreys’s Amazing Statistics Program (JASP).

Refer to the Tools and Software: JASP page on Campus for general information. Make sure that your statistical software is downloaded, installed, and running properly on your computer.

Competencies Measured

By successfully completing this assessment, you will demonstrate your proficiency in the course competencies through the following assessment scoring guide criteria:

• Competency 1: Analyze the computation, application, strengths, and limitations of various statistical tests.
• Analyze statistical assumptions.
• Competency 2: Analyze the decision making process of data analysis.
• Articulate the data analysis plan.
• Competency 3: Apply knowledge of hypothesis testing.
• Interpret statistical results and hypotheses.
• Competency 4: Interpret the results of statistical analyses.
• Explain statistical conclusions, the limitations of the test, and/or possible alternative explanations.
• Competency 6: Apply the results of statistical analyses (your own or others) to your field of interest or career.
• Analyze the potential applications of the test in the field and their implications.
• Competency 7: Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study.
• Communicate in a manner that is scholarly and professional, and adheres to APA style and formatting.

The requirement for this lesson’s assignment is to conduct PCA. This PCA will tell you whether or not an EFA is needed to explore latent factors within your items.

Use the following scenario as a reference when completing this week’s assignment.

What is the main purpose of a Principal Component Analysis?

Scenario: The University of Sussex constantly seeks to employ the best people as lecturers. The University wanted to revise the Teaching of Statistics for Scientific Experiments (TOSSE) questionnaire, which is based on Bland’s (1977) theory that says that good research methods lecturers should have:

● A profound love of statistics ● An enthusiasm for experimental design ● A love of teaching ● A complete absence of normal interpersonal skills.

These characteristics should be related (i.e., correlated). The University of Sussex revised this questionnaire to become the “Teaching of Statistics for Scientific Experiments – Revised” (TOSSE–R), as shown in Figure 3. NCU further modified this humorous tool for use in this week.

Figure 3

TOSSE-R Questionnaire (modified from Bland, 1977)

They gave this questionnaire to 239 research methods lecturers around the world to determine if it supported Bland’s (1977) theory. The data are in TOSSE-R.sav file. Address the following questions:

1. Based on the readings and this week’s lesson, what is the main purpose of factor analysis? What is the main purpose of a Principal Component Analysis?

2. What is the difference between PCA, EFA, and CFA?

3. According to the readings, what is the appropriate value for a factor loading?

4. Conduct a PCA and interpret the factor structure.

5. Present the results of the PCA, including a discussion of whether you think an EFA would be needed based on the results of the PCA and why.

6. How many factors were extracted from the questionnaire?

Length: Complete responses to all six questions and prompts. Please include the question prompts along with your responses in your assignment submission. In addition to a WORD (.doc) file with the answers to the assignment questions, also include the output (.spv) file.

NOTE: SPSS automatically generates the .spv file as you work in SPSS. When you close your SPSS main window, SPSS will ask you if you want to save the output file. Click ‘yes’, then save to your computer and upload with your assignment.

NOTE: In SPSS, you must be careful when running an EFA because the default is set to PCA; in the menu “Analyze” “Dimension reduction” “Factor” and then in the box labeled “Factor Analysis: Extraction” you will see “Method” and the default is already set to “principal component.” Principal component is the PCA, so if you leave this, you will be conducting a PCA.

References: No references are required, though any sources used other than those provided within the assignment should be cited and referenced in APA format