I’m working on a mathematics report and need a sample draft to help me understand better.
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 teams 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/fivethirtye…
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
- Simple Linear Regression
- 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.
| Criteria | Exemplary (100%) | Proficient (85%) | Needs Improvement (55%) | Not Evident (0%) | Value |
|---|---|---|---|---|---|
| Python Script | N/A | Accurately performs regression analyses, including data visualization, calculating coefficients, and linear and multiple linear regression (100%) | Shows progress toward proficiency, but with errors or omissions (55%) | Does not attempt criterion (0%) | 5 |
| Summary Report: Simple Linear Regression Correlation | Exceeds proficiency by writing with exceptional clarity, insight, and mastery of statistical terminology (100%) | Discusses relationships between the variables using data visualization and correlation coefficient (85%) | Shows progress toward proficiency, but with errors or omissions (55%) | Does not attempt criterion (0%) | 15 |
| Summary Report: Simple Linear Regression Model | Exceeds proficiency by writing with exceptional clarity, insight, and mastery of statistical terminology (100%) | Reports results of simple linear regression by identifying and interpreting the coefficient of determination, regression model, and the models significance (85%) | Shows progress toward proficiency, but with errors or omissions (55%) | Does not attempt criterion (0%) | 25 |
| Summary Report: Multiple Regression Correlation | Exceeds proficiency by writing with exceptional clarity, insight, and mastery of statistical terminology (100%) | Discusses relationships between the variables using data visualization and correlation matrix (85%) | Shows progress toward proficiency, but with errors or omissions (55%) | Does not attempt criterion (0%) | 15 |
| Summary Report: Multiple Regression Model | Exceeds proficiency by writing with exceptional clarity, insight, and mastery of statistical terminology (100%) | Reports results of multiple regression by identifying and interpreting the coefficients of determination, regression models, and results of hypothesis tests and F-tests (85%) | Shows progress toward proficiency, but with errors or omissions (55%) | Does not attempt criterion (0%) | 25 |
| Summary Report: Introduction and Conclusion | Exceeds proficiency by writing with exceptional clarity, insight, and mastery of statistical terminology (100%) | Communicates all ideas by presenting context, as well as summarizing and interpreting the practical implications of the results (85%) | Shows progress toward proficiency, but with errors or omissions (55%) | Does not attempt criterion (0%) | 10 |
| Articulation of Response | Exceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative manner (100%) | Clearly conveys meaning with correct grammar, sentence structure, and spelling, demonstrating an understanding of audience and purpose (85%) | Shows progress toward proficiency, but with errors in grammar, sentence structure, and spelling, negatively impacting readability (55%) | Submission has critical errors in grammar, sentence structure, and spelling, preventing understanding of ideas (0%) | 5 |
| Total: | 100% | ||||
