PROJECT TWO

For this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.

Python Script: To complete the tasks listed below, open the Project Two Jupyter Notebook link in the Assignment Information module. Your project contains the NBA data set and a Jupyter Notebook with your Python scripts. In the notebook, you will find step-by-step instructions and code blocks that will help you complete the following tasks:
Hypothesis tests for a population parameter
Hypothesis tests for a population mean
Hypothesis test for a population proportion
Hypothesis test for the difference between two population parameters
Hypothesis test for difference between two population means
Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:
Introduction: Set the context for your scenario and the analyses you will be performing.
Hypothesis tests for the population mean: Discuss all steps of the hypothesis tests and interpret your results.
Hypothesis test for the population proportion: Discuss all steps of the hypothesis test and interpret your results.
Hypothesis test for the difference between two population means: Discuss all steps of the hypothesis test and interpret your results.
Conclusion: Summarize your findings and explain their practical implications.

PROJECT TWO GUIDELINES

Competency

In this project, you will demonstrate your mastery of the following competency:

• Perform hypothesis testing to address an authentic problem

Scenario

You are a data analyst for a basketball team. You have found a large set of historical data, and are working to analyze and find patterns in the data set. The coach of the team and your management have requested that you perform several hypothesis tests to find the statistical significance of the claims that are being made about your team. This analysis will provide evidence to validate critical claims and get statistically valid findings that will help make key decisions to make the team better in upcoming seasons. You will use the Python programming language to perform statistical analysis and will also need to present a report of your findings to the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications. The managers will use your report to find areas where the team can improve its performance.

Note: This data set has been “cleaned” for the purposes of this assignment.

Reference

FiveThirtyEight. (April 26, 2019). FiveThirtyEight NBA Elo dataset. Kaggle. Retrieved from https://www.kaggle.com/fivethirtyeight/fivethirtyeight-nba-elo-dataset/

Directions

For this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.

1. Python Script: To complete the tasks listed below, open the Project Two Jupyter Notebook link in the Assignment Information module. Your project contains the NBA data set and a Jupyter Notebook with your Python scripts. In the notebook, you will find step-by-step instructions and code blocks that will help you complete the following tasks:
   • Hypothesis tests for a population parameter
     • Hypothesis tests for a population mean
     • Hypothesis test for a population proportion
   • Hypothesis test for the difference between two population parameters
     • Hypothesis test for difference between two population means
2. Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:
   • Introduction: Set the context for your scenario and the analyses you will be performing.
   • Hypothesis tests for the population mean: Discuss all steps of the hypothesis tests and interpret your results.
   • Hypothesis test for the population proportion: Discuss all steps of the hypothesis test and interpret your results.
   • Hypothesis test for the difference between two population means: Discuss all steps of the hypothesis test and interpret your results.
   • Conclusion: Summarize your findings and explain their practical implications.

What to Submit

To complete this project, you must submit the following:

Python Script
Your Jupyter Notebook Python script contains all the statistical analyses you completed for this project. You downloaded your work as an HTML file. Review the file to make sure that every step and all your outputs are included. Submit the HTML file as part of your submission. Review the Jupyter Notebook in Codio Tutorial in the Supporting Materials section if you need help.

Summary Report Zip File
Use the provided template to create your summary report. The template contains guiding questions to help you complete each section. Be sure to remove these questions before submitting your report. Your summary report should be submitted as a 3- to 5-page Microsoft Word document. It should include an APA-style cover page and APA citations for any sources used. Use double spacing, 12-point Times New Roman font, and one-inch margins.

 

 

 

 

 

 

 

 

 

 

 

MAT 243 Project Two Summary Report

 

[Full Name]

[SNHU Email]

Southern New Hampshire University

Note: Replace the bracketed text on page one (the cover page) with your personal information.

 

1.       Introduction: Problem Statement

 

Discuss the statement of the problem in terms of the statistical analyses that are being performed. In your response, you should address the following questions:

 

• What is the problem you are going to solve?
• What data set are you using?
• What statistical methods will you be using to do the analysis for this project?

 

 Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include Python code in your report.

 

2.       Introduction: Your Team and the Assigned Team

 

In the Python script, you picked the same team and years that you picked for Project One. The assigned team and its range of years will be the same as in Project One as well.

 

See Steps 1 and 2 in the Python script to address the following items in the table below:

 

• What team did you pick and what years were picked to do the analysis?
• What team and range of years were you assigned for the comparative study? (Hint: this is called the assigned team in the Python script.) Present this information in a formatted table as shown below.

 

Table 1. Information on the Teams

 

	Name of Team	Years Picked
1. Yours	Team (e.g. Knicks)	XXXX-YYYY (e.g. 2013 – 2015)
2. Assigned	Team (e.g. Bulls)	XXXX-YYYY (e.g. 1996- 1998)

 

 Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include Python code in your report.

 

3.       Hypothesis Test for the Population Mean (I)

 

Suppose a relative skill level of 1420 represents a critically low skill level in the league. The management of your team has hypothesized that the average relative skill level of your team is greater than 1420. You tested this claim using a 5% level of significance. For this test, you assumed that the population standard deviation for relative skill level is unknown. Explain the steps you took to test this problem and interpret your results.

 

See Step 3 in the Python script to address the following items:

 

• In general, how is hypothesis testing used to test claims about a population mean?
• Summarize all important steps of the hypothesis test. This includes:
  1. Null Hypothesis (statistical notation and its description in words)
  2. Alternative Hypothesis (statistical notation and its description in words)
  3. Level of Significance
  4. Report the Test Statistic and the P-value in a formatted table as shown below:

Table 2: Hypothesis Test for the Population Mean (I)

 

Statistic	Value
Test Statistic	X.XX *Round off to 2 decimal places.
P-value	X.XXXX *Round off to 4 decimal places.

 

1. Conclusion of the hypothesis test and its interpretation based on the P-value

• What are the implications of your findings from this hypothesis test? What is its practical significance?

 

 Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include Python code in your report.

 

4.       Hypothesis Test for the Population Mean (II)

 

Your team’s coach has hypothesized that average number of points scored by your team in the team’s years is less than 110 points. For this test, you assumed that the population standard deviation for points scored is unknown. You tested the claim using a 1% level of significance. Explain the steps you took to test this problem and interpret your results.

 

See Step 4 in the Python script to address the following items:

 

• Summarize all important steps of the hypothesis test. This includes:
  1. Null Hypothesis (statistical notation and its description in words)
  2. Alternative Hypothesis (statistical notation and its description in words)
  3. Level of Significance
  4. Report the Test Statistic and the P-value in a formatted table as shown below:

Table 3: Hypothesis Test for the Population Mean (II)

 

Statistic	Value
Test Statistic	X.XX *Round off to 2 decimal places.
P-value	X.XXXX *Round off to 4 decimal places.

 

1. Conclusion of the hypothesis test and its interpretation based on the P-value

• What are the implications of your findings from this hypothesis test? What is its practical significance?

 

 Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include Python code in your report.

 

5.       Hypothesis Test for the Population Proportion

 

Suppose the management claims that the proportion of games that your team wins when scoring 80 or more points is 0.50. You tested this claim using a 5% level of significance. Explain the steps you took to test this problem and interpret your results.

 

See Step 5 in the Python script to address the following items:

 

• In general, how is hypothesis testing used to test claims about a population proportion?
• Summarize all important steps of the hypothesis test. This includes:
  1. Null Hypothesis (statistical notation and its description in words)
  2. Alternative Hypothesis (statistical notation and its description in words)
  3. Level of Significance
  4. Report the Test Statistic and the P-value in a formatted table as shown below:

 

Table 4: Hypothesis Test for the Population Proportion

 

Statistic	Value
Test Statistic	X.XX *Round off to 2 decimal places.
P-value	X.XXXX *Round off to 4 decimal places.

 

1. Conclusion of the hypothesis test and its interpretation based on the P-value

• What are the implications of your findings from this hypothesis test? What is its practical significance?

 

 Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include Python code in your report.

 

6.       Hypothesis Test for the Difference Between Two Population Means

 

You were asked to compare your team’s skill level (from its years) with the assigned team’s skill level (from the assigned time frame). You tested the claim that the skill level of your team is the same as the skill level of the assigned team, using a 1% level of significance.

 

See Step 6 in the Python script to address the following items:

 

• In general, how is hypothesis testing used to test claims about the difference between two population means?
• Summarize all important steps of the hypothesis test. This includes:
  1. Null Hypothesis (statistical notation and its description in words)
  2. Alternative Hypothesis (statistical notation and its description in words)
  3. Level of Significance
  4. Report the Test Statistic and the P-value in a formatted table as shown below:

 

Table 5: Hypothesis Test for the Difference Between Two Population Means

 

Statistic	Value
Test Statistic	X.XX *Round off to 2 decimal places.
P-value	X.XXXX *Round off to 4 decimal places.

 

1. Conclusion of the hypothesis test and its interpretation based on the P-value

• What are the implications of your findings from this hypothesis test? What is its practical significance?

 

 Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include Python code in your report.

 

 

7.       Conclusion

 

Describe the results of your statistical analyses clearly, using proper descriptions of statistical terms and concepts.

 

• What is the practical importance of the analyses that were performed?
• Describe what these results mean for the scenario.

 

 Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include Python code in your report.

 

8.       Citations

 

You were not required to use external resources for this report. If you did not use any resources, you should remove this entire section. However, if you did use any resources to help you with your interpretation, you must cite them. Use proper APA format for citations.

 

Insert references here in the following format:

 

Author’s Last Name, First Initial. Middle Initial. (Year of Publication). Title of book: Subtitle of book, edition. Place of Publication: Publisher.