guide to using excel 2007 for basic statistical applications to accompany business statistics: a...
TRANSCRIPT
Guide to Using Excel 2007 For Basic Statistical Applications
Guide to Using Excel 2007 For Basic Statistical Applications
To Accompany
Business Statistics: A Decision Making Approach, 8th Ed.
Chapter 15:
Multiple Regression and Model Building
By
Groebner, Shannon, Fry, & SmithPrentice-Hall Publishing Company
Copyright, 2011
Chapter 15 Excel Examples
Multiple Regression First City Real Estate
Multiple Regression –Dummy Variable First City Real Estate
Curvilinear RegressionAshley Investment Services
Interaction Effects Ashley Investment Services
More Examples
Chapter 15 Excel Examples
Residual Analysis First City Real Estate
Multiple Regression – First City Real Estate
Issue: First City management wishes to build a model that can be used to predict sales prices for residential property.
Objective: Use Excel 2007 to build a multiple regression model relating sales price to a set of measurable variables.
Data file is FirstCity.xls
Multiple Regression – First City Real Estate
• Open the file FirstCity.xls, Sheet Homes-Sample 1
• Select the Data Tab• Select Data Analysis• Select Correlation• OK
Multiple Regression – First City Real Estate
• Input Range: A1:G320• Grouped by: Columns• New Worksheet Ply: corr-
1• OK
Multiple Regression – First City Real Estate
This cell shows the correlation, 0.7477, between Price and Square Feet
Multiple Regression – First City Real Estate
Return to Homes-Sample 1• Select the Data tab• Select Data Analysis• Select Regression• OK
Multiple Regression – First City Real Estate
• Input Y Range: A1:A320• Input X Range: B1:F320• Select labels• New Worksheet Ply:
regress-1• OK
Multiple Regression – First City Real Estate
Excel produces the Regression Model
Multiple Regression – First City Real Estate
To determine if multicollinearity is a problem:• Select the Add-Ins tab• Select PHStat• Select Regression• Select Multiple Regression
Multiple Regression – First City Real Estate
• Y variable … : A1:A320• X variable … : B1:F320• Select First Cells in both …• Select Regression Statistics
…• Select ANOVA and …• Select Variance Inflation … • OK
Multiple Regression – First City Real Estate
PHStat will find Variance Inflation Factors for all independent variables. This slide shows the VIF for Garage # and all other X variables. Click on the sheet tabs X4,X3,X2,X1 to see the VIF for the other variables.
Issue: First City managers wish to improve the model by adding a location variable for the area.
Objective: Use Excel 2007 to improve a regression model by adding a dummy variable for the area either foothills or flatland.
Data file is First City.xls
Multiple Regression - Dummy Variable -First City Real EstateMultiple Regression - Dummy Variable -First City Real Estate
Multiple Regression- Dummy Variable – First City Real Estate
• Select the Home-Sample 2 sheet
• Select the Add-In tab• Select PHStat• Select Regression• Select Multiple
Regression
Multiple Regression- Dummy Variable – First City Real Estate
• Cut Bedrooms and Bathrooms columns and paste in cell G1. Delete columns C and D so that all data is in connected columns
• Select Data tab• Select Regression• Input Y Range: A1 – A320• Input X Range B1-E320 • Select Labels• New Worksheet: Regress-2• OK
Multiple Regression- Dummy Variable – First City Real Estate
All variables are significant and have the expected sign
Curvilinear Relationships - Ashley Investment ServicesCurvilinear Relationships - Ashley Investment Services
Issue: The director of personnel is trying to determine whether there is a relationship between employee burnout and time spent socializing with co-workers.
Objective: Use Excel 2007 to determine whether the relationship between the two measures is statistically significant.
Data file is Ashley.xls
Curvilinear Relationships – Ashley Investment Services
Open the file Ashley.xls
Curvilinear Relationships – Ashley Investment Services
• Select A1:B21• Select the Insert Tab• Select Scatter Plot• Select the Scatter Plot desired
Curvilinear Relationships – Ashley Investment Services
Curvilinear Relationships – Ashley Investment Services
• Select the Data tab• Select Data Analysis• Select Regression
Curvilinear Relationships – Ashley Investment Services
• Y Range A1:A21• X Range B1:B21• Labels• New Worksheet Ply:
Ashley-1• OK
Curvilinear Relationships – Ashley Investment Services
Curvilinear Relationships – Ashley Investment Services
To develop a nonlinear model, return to the data file. Create a new variable Socialization Squared
Curvilinear Relationships – Ashley Investment Services
• Select the Data tab• Select Data Analysis• Select Regression• OK
Curvilinear Relationships – Ashley Investment Services
• Input Y Range: A1:A21• Input X Range: B1:C21• Select Labels• New Worksheet Ply: Ashley-2
Curvilinear Relationships – Ashley Investment Services
The output shows the R Square value and the Regression Coefficients.
Interaction Effects - Ashley Investment ServicesInteraction Effects - Ashley Investment Services
Issue: The director of personnel is trying to determine whether the model can be improved by separating observations between those taken from men and women.
Objective: Use Excel 2007 to determine whether the relationship between the measures can be improved.
Data file is Ashley-2.xls
Interaction Effects – Ashley Investment Services
• Open file Ashley-2.xls• Insert a new column C as
(Socialization Squared) which is Column B squared
• Add Column E as Columns B * D
• Add Column F as Columns C * D
Interaction Effects – Ashley Investment Services
Using The Insert tab and Chart tools set up a Scatter Plot for one gender
Interaction Effects – Ashley Investment Services
Add the second gender
Add exponential trend line for male and female
Interaction Effects – Ashley Investment Services
The regression for the curvilinear model.
Issue: The company is interested in analyzing the residuals of the regression model to determine whether the assumptions of multiple regression are satisfied.
Objective: Use Excel 2007 to analyze residuals from a regression model.
Data file is First City-3.xls
Residual Analysis - First City Real Estate
Residual Analysis - First City Real Estate
Residual Analysis – First City Real Estate
Open the file FirstCity3.xls
Since Excel requires independent variables to be in adjacent columns – cut and paste these columns.
We will be using:• Price• Sq. Feet• Bedrooms• Garage #• Log of Lot Size
• Note: I will swap Lot Size and Log Lot Size to simplify the operation
Residual Analysis – First City Real Estate
• Select the Data tab
• Select Data Analysis
• Select Regression
• OK
Residual Analysis – First City Real Estate
Define the range for X and Y variables.Excel gives several options for Residual Analysis but does not have as complete a set as Minitab
Residual Analysis – First City Real Estate
This is the Residual Plot for Square Feet
Residual Analysis – First City Real Estate
While Excel will not automatically generate a histogram of the standardized residuals , one can be created.
Residual Analysis – First City Real Estate
Define Bin values for the Histogram
Residual Analysis – First City Real Estate
• Select the Data tab
• Select Data Analysis
• Select Histogram• On the Histogram
Chart identify the data and bins
• Select Chart output
Residual Analysis – First City Real Estate