Data Visualization and Descriptive Statistics Case Study

Description

This assignment is intended to test your knowledge of how to appropriately compare two means in Excel using a data file with the student debt amounts. The data file has 50 randomly selected student debt amounts from 2019 and 50 randomly selected student debt amounts from 2012. A university representative has asked you whether the sample data provide enough evidence to believe there is a difference between the debt amounts in the two years.

After watching the accompanying videos, read the instructions and fully address all questions. Run all required analyses and submit them along with the data file in a single Excel workbook that shows all your output and provides responses to all of the questions in a Word document.

Here is the only additional information I just found. Let me know if this helps. I also googled that and this might help: https://www.google.com/search?q=data+analysis+toolpak+in+excel&rlz=1C1GCEA_enUS885US885&oq=Data+Analysis+Toolpak+in+Excel&aqs=chrome.0.0l8.8865j0j7&sourceid=chrome&ie=UTF-8

Hints for Case Study:

Step 1: Use the F-test to conclude that the variances are equal or not equal. Watch this video: https://www.youtube.com/watch?v=qI_RmXU1tOY

Step 2: Select an appropriate t-test based on the conclusion of step 1. Run the selected t-test t and conclude that the means are equal or not equal. You only need one t-test. Do not perform two different t-tests. If you do, I’ll assume you have no idea which t-test is the correct one to use. Videos: https://www.youtube.com/watch?v=OHHhzLHakKA and https://www.youtube.com/watch?v=L-jfenou5hI

Explanation & Answer length: 1 Page

Week 5 Case Study – Data Visualization and Descriptive Statistics (Case Study #3)
Case Study #3 is intended to test your knowledge of how to appropriately compare two means.
The data file has 50 randomly selected student debt amounts from 2019 and 50 randomly
selected student debt amounts from 2012. The data fields included are as follows:
• Debt in 2019 (dollars)
• Debt in 2012 (dollars)
A university representative wants to know whether the sample data provide enough evidence
to believe there is a difference between the debt amounts in the two years. The null and
alternative hypotheses are shown below.
• Null Hypothesis: Mean Student Debt in 2019 is equal to Mean Student Debt in 2012
• Alternative Hypothesis: Mean Student Debt in 2019 is not equal to Mean Student Debt
in 2012
Complete the following tasks:

1. Run an F-test for two sample variances using an alpha level of 0.05 and answer the
   following questions:
   a. Which of the two years has the higher mean? What are the values?
   b. Which of the two years has the higher variance? What are the values?
   c. Based on the statistical output, would you conclude that variances are equal or
   not equal? Provide an appropriate/authoritative explanation leveraging the
   statistical output.
2. Run an appropriate t-test (assuming either equal or unequal variances based on your
   conclusion in 1c above) using an alpha level of 0.05 and answer the following questions:
   a. Is this a one-tailed or two-tailed test? Provide an appropriate/authoritative
   explanation that fully explains the choice.
   b. Based on the statistical output, would you conclude that means are equal or not
   equal? Provide an appropriate/authoritative explanation leveraging the
   statistical output.
   c. Using everyday language that could be understood by parents and students,
   what does the analysis say about student debt in 2019 versus 2012? Provide an
   appropriate/authoritative explanation leveraging the statistical output (e.g., use
   confidence level, rationale, etc.)
   Make sure that you run all the required analyses using the Data Analysis Toolpak in Excel and
   SUBMIT the Data Analysis Output along with the Data file in a Single Excel workbook that
   shows all your output. You should also submit a separate Word document that fully, and
   professionally, responds to each question.
   Case Study #3 is due on Sunday by 11:59pm of Week 5

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