Project Three: Simple Linear Regression and Multiple Regression

This notebook contains step-by-step directions for Project Three. It is very important to run through the steps in order. Some steps depend on the outputs of earlier steps. Once you have completed the steps in this notebook, be sure to write summary report.

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 total number of wins for a team in the regular season based on key performance metrics. Although the data set is the same that you used in the previous projects, the data set used here has been aggregated to study the total number of wins in a regular season based on performance metrics shown in the table below. 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 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.

There are four important variables in the data set that you will utilize in Project Three.

Variable

What does it represent

total_wins

Total number of wins in a regular season

avg_pts

Average points scored in a regular season

avg_elo_n

Average relative skill of each team in a regular season

avg_pts_differential

Average point differential between the team and their opponents in a regular season

The average relative skill (represented by the variableavg_elo_nin the data set) is simply the average of a team's relative skill in a regular season. Relative skill is measured using the ELO rating. This measure is inferred based on the final score of a game, the game location, and the outcome of the game relative to the probability of that outcome. The higher the number, the higher the relative skill of a team.

Reminder: It may be beneficial to review the summary report document for Project Three prior to starting this Python script. That will give you an idea of the questions you will need to answer with the outputs of this script.

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STEP 1: DATA PREPARATION

STEP 2: SCATTERPLOT AND CORRELATION FOR THE TOTAL NUMBER OF WINS AND AVERAGE POITS SCORED

STEP 3: SIMPLE LINEAR REGRESSION: PREDICTING THE TOTAL NUMBER OF WINS USING AVERAGE POINTS SCORED

STEP 4: SCATTERPLOT AND CORRELATION FOR THE TOTAL NUMBER OF WINS AND AVERGE RELATIVE SKILL

STEP 5: MULTIPLE REGRESSION: PREDICTING THE TOTAL NUMBER OF WINS USING AVERAGE POINTS SCORED AND AVERAGE RELATIVE SKILL

STEP 6: MULTIPLE REGRESSION: PREDICTING THE TOTAL NUMBER OF WINS USING AVERAGE POINTS SCORED, AVERAGE RELATIVE SKILL, AND AVERAGE POINTS DIFFERENTIAL

WHAT I NEED HELP WITH

Set the context for your scenario and the analyses you will be performing.

Discuss relationships between variables using scatterplots and correlation coefficients.

Create simple linear regression model to predict the response variable.

Create multiple regression model to predict the response variable.

Summarize your findings and explain their practical implications.