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Posted: April 14th, 2022

Chapter 8 Trendlines and Regression Analysis

Chapter 8 Trendlines and Regression Analysis

Instructions: Please submit your work in one single Excel file with one tab/worksheet for each problem.

Simple Linear Regression, Residual Analysis and Regression Assumptions

1. (30 points) The Excel file National Football League provides various data on professional football for one season.

a. Construct a scatter diagram for points/game and yards/game in the Excel file. Does there appear to be a linear relationship?

b. Use the Regression tool to develop a model for predicting points/game as a function of yards/game. Explain the statistical significance of the model and value.

c. Analyze the residuals to determine if the assumptions underlying the regression analysis are valid. In addition, use the standard residuals to determine if any possible outliers exist.

Building Good Regression Models

2. (40 points) Use the data in the Excel file Job Satisfaction to find the best multiple regression model to predict the overall satisfaction as a function of the other variables.

a. Show your steps to build the best regression model.

b. What managerial implications does your result have?

Regression with Categorical Independent Variables

3. (30 points) A national homebuilder builds single-family homes and condominium-style townhouses. The Excel file House Sales provides information on the selling price, lot cost, type of home, and region of the country (M = Midwest, S = South) for closings during on month.

a. Develop a multiple regression model for sales price as a function of lot cost and type of home without any interaction term.

b. Determine if an interaction exists between lot cost and type of home and find the best model.

c. What is the predicted price for either a single-family home or a townhouse with a lot cost of $30,000?

———–

Trendlines and Regression Analysis in Chapter 8

Please submit your work in a single Excel file with one tab/worksheet for each problem.

Regression Assumptions, Residual Analysis, and Simple Linear Regression

1. Formalized paraphrase (30 points) The National Football League Excel file contains various data on professional football for a single season.

a. In the Excel file, create a scatter diagram for points/game and yards/game. Is there a clear linear relationship?

b. Using the Regression tool, create a model for predicting points per game as a function of yards per game. Explain the model’s and value’s statistical significance.

c. Examine the residuals to see if the assumptions underpinning the regression analysis are correct. In addition, use the standard residuals to determine if any possible outliers exist.

Building Good

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