Category: Statistics

1. Download the SPSS Dataset.Therapist.sav_b dataset
2. Download and complete the MFT7110.Week 8.SPSS Assignment document
3. You will also submit the SPSS output file you obtained, which should be saved as Lastname.First initial.MFT7110.Week 8.spv
4. Save the MFT7110.Week 8.SPSS Assignment document as Lastname.First initial.MFT7110.Week 8.SPSS
• Read Chapters 9-10
• Caldwell, S. (2013). Statistics unplugged. Belmont, CA: Wadsworth, Cengage Learning.
• Read Chapters 8 , 9 & 10
• Schwartz, B. M., Wilson, J. H., & Goff, D. M. (2015). An easy guide to research design & SPSS. Los Angeles, CA: Sage.
• See additional resources in the Books and Resources for this Week section.
• Assignment 8: Conduct ANOVA Using SPSS
In this assignment, you will conduct an analysis of variance (ANOVA), a statistical
test typically used when there are more than two categories or levels of the
independent variable, and the dependent variable is measured at the interval or
ratio level.
Again, you will use the SPSS Dataset.Adolescent FT.sav file, which contains 13
variables:
(a) Participant.ID (Each person’s identification number),
(b) Fam.ID (Family identification number),
(c) Race (1. African American, 2. European American, 3. Mexican American, 4.
Multiracial)
(d) Fam.Pos (Family position: 1. Mother, 2. Adolescent)
(e) Adol.Gender (Gender of adolescent: 1. Female, 2. Male)
(f) Ther.ID (Therapist identification number)
(g) Pre.Prob (The adolescent’s presenting problem: 1. Depression, 2. Oppositional
Defiant Disorder, 3. Anxiety)
(h) PHQ9 (Scores on the Patient Health Questionnaire-9, a brief depression
screening measure; Kroenke, Spitzer, & Williams, 2001)
(i) Anxiety (Scores on a measure of anxiety developed for this study)
(j) FAD (Scores on the Family Assessment Device; item scores are averaged, with
higher scores representing perceptions of poorer family functioning; Mansfield,
Keitner, & Dealy, 2015)
(k) Life.Sat (Scores on a hypothetical measure of life satisfaction)
(l) Alliance (Scores on a hypothetical measure of the therapeutic alliance)
(m) Drop.Out (Did the family drop out prior to the completion of the seven-session
study treatment protocol?)
Once again, ANOVA assumes that the observations are independent, so you can
only use data from one person in the family (another solution would be to average
relational observations, but that is often problematic. For example, suppose scores
on a couple satisfaction assessment ranged from 0-100. If you averaged the scores
for the members of each couple, a couple with scores of 10 and 90 would have
same average score, 50, as a couple with scores of 45 and 55. Can you see why
averaging scores is not optimal? Note that summing scores is the mathematical
equivalent of averaging scores, and thus is equally problematic).
For this assignment, you will evaluate whether there are differences in anxiety
levels based on the adolescent’s race or gender. To complete the assignment,
address the following:
a. State the null and alternative hypotheses (one pair for race and one pair for
gender). Assume you do not have sufficient evidence to anticipate the outcome, so
factor that into your alternative hypotheses.
• b. Conduct the univariate ANOVA in SPSS (refer to the SPSS example in the
Between Groups with More Than Two Levels of an IV section in Chapter 7 (p.
88) in the Schwartz et al. text). Your dependent variable is Anxiety and your fixed
factors are Race and Adolescent Gender. You will not enter anything into the
Random Factors, Covariate, or WLS Weight boxes. Note that you will obtain a non-
significant interaction term in the output (Race * Adol Gender). Just ignore that
line.
c. Request a post hoc test (LSD) for Race. Then, in your response, explain why you
don’t need to request a post hoc test for gender.
d. Report the results of the ANOVA (including the post hoc results for race) in APA
format (model your language after the example in the Schwartz et al. text).
e. Indicate what you learned about these variables after conducting this analysis.
References
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9. Journal of
General Internal Medicine, 15, 606-613.
Mansfield, A. K., Keitner, G. I., & Dealy, J. (2015). The family assessment device:
An update. Family Process, 54, 82-93.

In part 1 of the course project, you will consider a question or decision and begin to apply a predictive analysis approach to that decision. In this first part of the project, you will focus on identifying independent variables that may influence outcomes.
In part 2 of the course project, you will define how values of independent variables relate to the variable of interest. You’ll build a regression model and consider whether the regression equation accurately captures the relationships between the independent variables and the dependent variable.
In part 3 of the course project, you will apply these techniques to the regression model you created in Part Two of the course project. When you complete this project part, you should have a refined regression model.
In part 4 of the course project, you synthesize your findings in a concise and minimally technical argument for the validity of your model.
Complete all parts in the attached course project document

All answers must be typed directly into the provided spaces.
Only long or complex handwritten equations/graphs can be submitted as a PDF attachment.
Python codes must be written in the cells provided on the Forum. Submissions of Python code in PDF format will not be accepted.
As you work the problems and write up your solutions, try to use the correct vocabulary and notation for your ideas. Ensure the submitted PDF is readable and properly formatted.
Assignment Information
Learning Outcomes Added
Distributions: Identify different types of distributions and make inferences based on samples from distributions appropriately.
Probability: Apply and interpret fundamental concepts of probability, including conditional and bayesian probabilities.
ModelSelection: Apply appropriate statistical theory and methods to determine which model generated observed data.
ParameterEstimation: Apply appropriate statistical theory and methods to determine which parameter values generated observed data.
CompTools: Use appropriate computational tools to solve problems in Probability and Statistics.
MathTools: Use appropriate mathematical notation (including DAGs) and tools to solve problems in Probability and Statistics.
ProfessionalWorkProduct: Follows the established guidelines for the task and academic conventions in writing and presentations.

All answers must be typed directly into the provided spaces.
Only long or complex handwritten equations/graphs can be submitted as a PDF attachment.
Python codes must be written in the cells provided on the Forum. Submissions of Python code in PDF format will not be accepted.
As you work the problems and write up your solutions, try to use the correct vocabulary and notation for your ideas. Ensure the submitted PDF is readable and properly formatted.
Assignment Information
Learning Outcomes Added
Distributions: Identify different types of distributions and make inferences based on samples from distributions appropriately.
Probability: Apply and interpret fundamental concepts of probability, including conditional and bayesian probabilities.
ModelSelection: Apply appropriate statistical theory and methods to determine which model generated observed data.
ParameterEstimation: Apply appropriate statistical theory and methods to determine which parameter values generated observed data.
CompTools: Use appropriate computational tools to solve problems in Probability and Statistics.
MathTools: Use appropriate mathematical notation (including DAGs) and tools to solve problems in Probability and Statistics.
ProfessionalWorkProduct: Follows the established guidelines for the task and academic conventions in writing and presentations.

All answers must be typed directly into the provided spaces.
Only long or complex handwritten equations/graphs can be submitted as a PDF attachment.
Python codes must be written in the cells provided on the Forum. Submissions of Python code in PDF format will not be accepted.
As you work the problems and write up your solutions, try to use the correct vocabulary and notation for your ideas. Ensure the submitted PDF is readable and properly formatted.
Assignment Information
Learning Outcomes Added
Distributions: Identify different types of distributions and make inferences based on samples from distributions appropriately.
Probability: Apply and interpret fundamental concepts of probability, including conditional and bayesian probabilities.
ModelSelection: Apply appropriate statistical theory and methods to determine which model generated observed data.
ParameterEstimation: Apply appropriate statistical theory and methods to determine which parameter values generated observed data.
CompTools: Use appropriate computational tools to solve problems in Probability and Statistics.
MathTools: Use appropriate mathematical notation (including DAGs) and tools to solve problems in Probability and Statistics.
ProfessionalWorkProduct: Follows the established guidelines for the task and academic conventions in writing and presentations.

All answers must be typed directly into the provided spaces.
Only long or complex handwritten equations/graphs can be submitted as a PDF attachment.
Python codes must be written in the cells provided on the Forum. Submissions of Python code in PDF format will not be accepted.
As you work the problems and write up your solutions, try to use the correct vocabulary and notation for your ideas. Ensure the submitted PDF is readable and properly formatted.
Assignment Information
Learning Outcomes Added
Distributions: Identify different types of distributions and make inferences based on samples from distributions appropriately.
Probability: Apply and interpret fundamental concepts of probability, including conditional and bayesian probabilities.
ModelSelection: Apply appropriate statistical theory and methods to determine which model generated observed data.
ParameterEstimation: Apply appropriate statistical theory and methods to determine which parameter values generated observed data.
CompTools: Use appropriate computational tools to solve problems in Probability and Statistics.
MathTools: Use appropriate mathematical notation (including DAGs) and tools to solve problems in Probability and Statistics.
ProfessionalWorkProduct: Follows the established guidelines for the task and academic conventions in writing and presentations.

Nike Case Assignment (60 points)
Due 10/6 11:59 PM
Read the following case (included with McGraw-Hill Connect) and respond to the discussion prompts.
Nike, Inc. (MHE-FTR-060)
Discussion Prompts
What are Nike’s vision and mission? (5 pts)
Analyze the industry Nike competes in using Porter’s 5-Forces framework.
Clearly define the industry that Nike operates in. (5 pts)
Identify whether the force is high, moderate, or low for each force. Explain your rationale for each force. (20 pts)
Using the conclusions of each force, suggest whether the industry is attractive (i.e., profitable) or not. Explain your rationale. (10 pts)
Analyze Nike’s internal environment.
What are Nike’s core competencies (identify at least two)? (5 pts)
Do the identified core competencies give Nike a sustainable competitive advantage? (Conduct a VRIO analysis by explaining your rationale for each criterion.) (15 pts)
Instructions
You must only use information from the case. Any external information will result in a penalty.
You have three attempts available. The last submission will be graded.
Submission must be in Microsoft Word format.
Excluding the questions/prompts & references, the write-up should be above 800 words.
Make sure to connect the responses to the learnings.
Cite key evidence from the case for your answer.
Use the numbers to answer the questions, but leave out the questions.
Do not plagiarize. All sentences should be paraphrased. Only use quotes if absolutely necessary. Plagiarism will result in zero points.
SafeAssign scores will be available after submission. If the SafeAssign score is above 25%, the instructor will check the report to see if any plagiarism is detected. There will be penalties depending on the severity.
Grading Rubric
Linkages made between learning and answers
Deductions from assigned points to each question
Use of external info: -20 pts
File format: Microsoft Word
Incorrect file format: -5 pts
Meeting the word limit.
750-799 words: -5 pts
500-749 words: -10 pts
300-499 words: -20 pts
Less than 300 words: -40 pts
Late assignments.
Deductions will be made according to how late the assignment is.
Plagiarism will result in zero points.

Writing guidelines:
1. Brief summary of the case (up to 1 page), plus initial data.
2. Write each question/sub-question in bold and continue with your answer.
3. The length of each answer is about 0.3 page + ( as needed).
4. Formatting: Times New Roman, 12, double space.
5. References
Preparing a Managerial Report
Example: The first question under Managerial Report says “Develop appropriate descriiptive statistics to summarize the data.”
Answer: For this question utilize both tables and graphs. You should go one by one over each survey question (age, access to Internet, etc.). Once the particular table and graph (bar chart or pie chart for the qualitative data, histogram for the quantitative data) are ready, analyze results. After each survey question is analyzed, write a general summary for the case question.

Complete a Critical Review using the following template and based on the article Worry, Intolerance of Uncertainty, and Statistics Anxiety by Amanda Williams

Conduct a Difference in Differences Analysis. The analysis focuses on
a treatment and a control group. Sanctioned companies are the treatment and non-
sanctioned companies (random sectors) the control group. Please do the analysis in the R statistical
program. The goal is to test whether sanctions lowered the financial indicators of firms in different sectors, so I need a result for each of the 3 sectors (Energy, Transportation, and Banks) and a result for each of the 3 financial indicators (total assets, turnover, and profit). I need to be able to tell if the indicators went down or up after sanctions were imposed in each sector. Prior to 2022 means before sanctions. 2022/23 means after sanctions. Please briefly explain how the results of the analysis show this change and what the results mean. I will include a paper that does a similar type of analysis, the main difference between my task and that paper is that I want to compare sectors.