Competency
In this project, you will demonstrate your mastery of the following competency:
- Perform regression analysis to address an authentic problem
Scenario
You are a data analyst for a basketball team and have access to a large set of historical data that you can use to analyze performance patterns. The coach of the team and your management have requested that you come up with regression models that predict the number of wins in a regular game based on the performance metrics that are included in the data set. These regression models will help make key decisions to improve the performance of the team. You will use the Python programming language to perform the statistical analyses and then prepare a report of your findings to present for the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications.
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.
Python Script: To complete the tasks listed below, open the Project Three Jupyter Notebook link in the Assignment Information module. This notebook contains your data set and the Python scripts for your project. In the notebook, you will find step-by-step instructions and code blocks that will help you complete the following tasks:
Simple Linear Regression
- Create
scatterplots
- Compute the
correlation coefficient
- Conduct a
linear regression
Multiple Regression
- Create
scatterplots
- Compute the
correlation matrix
- Conduct a
multiple regression
analysis
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.
Scatterplots and Correlation: Discuss relationships between variables using scatterplots and correlation coefficients.
Simple Linear Regression: Create a simple linear regression model to predict the response variable.
Multiple Regression: Create a multiple regression model to predict the response variable.
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 Word Document
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.
Supporting Materials
The following resource(s) may help support your work on the project:
Document:
Jupyter Notebook in Codio Tutorial PDF
This tutorial will help you become familiar with the Jupyter Notebook interface. You will learn how to open, complete, save, and download your Jupyter Notebook for this project.
Shapiro Library:
APA Style Guide
This guide will help you format your cover page and references according to APA style. You are
not
required to use external resources for this project. However, if you do use any resources, you
must
cite them in APA format.
Project Three Rubric