Groebner Business Statistic 8ed Ch15 Xl 2007 Tutorial
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Transcript of Groebner Business Statistic 8ed Ch15 Xl 2007 Tutorial
![Page 1: Groebner Business Statistic 8ed Ch15 Xl 2007 Tutorial](https://reader031.fdocuments.us/reader031/viewer/2022012304/5451d4feaf79591d308b4bbe/html5/thumbnails/1.jpg)
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
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Chapter 15 Excel Examples
Multiple Regression
First City Real Estate
Multiple Regression –Dummy Variable
First City Real Estate
Curvilinear Regression
Ashley Investment Services
Interaction Effects
Ashley Investment Services
More Examples
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Chapter 15 Excel Examples
Residual Analysis
First City Real Estate
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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
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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
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Multiple Regression – First City Real Estate
•Input Range: A1:G320
•Grouped by: Columns
•New Worksheet Ply: corr-1
•OK
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Multiple Regression – First City Real Estate
This cell shows the correlation, 0.7477, between Price and Square Feet
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Multiple Regression – First City Real Estate
Return to Homes-Sample 1
•Select the Data tab
•Select Data Analysis
•Select Regression
•OK
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Multiple Regression – First City Real Estate
•Input Y Range: A1:A320
•Input X Range: B1:F320
•Select labels
•New Worksheet Ply: regress-1
•OK
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Multiple Regression – First City Real Estate
Excel produces the Regression Model
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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
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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
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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.
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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 Estate
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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
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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
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Multiple Regression- Dummy Variable –
First City Real Estate
All variables are significant and have the expected sign
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Curvilinear 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
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Curvilinear Relationships – Ashley Investment Services
Open the file Ashley.xls
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Curvilinear Relationships – Ashley Investment Services
•Select A1:B21
•Select the Insert Tab
•Select Scatter Plot
•Select the Scatter Plot desired
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Curvilinear Relationships – Ashley Investment Services
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Curvilinear Relationships – Ashley Investment Services
•Select the Data tab
•Select Data Analysis
•Select Regression
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Curvilinear Relationships – Ashley Investment Services
•Y Range A1:A21
•X Range B1:B21
•Labels
•New Worksheet Ply: Ashley-1
•OK
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Curvilinear Relationships – Ashley Investment Services
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Curvilinear Relationships – Ashley Investment Services
To develop a nonlinear model, return to the data file. Create a new variable Socialization Squared
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Curvilinear Relationships – Ashley Investment Services
•Select the Data tab
•Select Data Analysis
•Select Regression
•OK
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Curvilinear Relationships – Ashley Investment Services
• Input Y Range: A1:A21• Input X Range: B1:C21• Select Labels• New Worksheet Ply: Ashley-2
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Curvilinear Relationships – Ashley Investment Services
The output shows the R Square value and the Regression Coefficients.
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Interaction 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
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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
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Interaction Effects – Ashley Investment Services
Using The Insert tab and Chart tools set up a Scatter Plot for one gender
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Interaction Effects – Ashley Investment Services
Add the second gender
Add exponential trend line for male and female
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Interaction Effects – Ashley Investment Services
The regression for the curvilinear model.
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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
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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
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Residual Analysis – First City Real Estate
•Select the Data tab•Select Data Analysis•Select Regression•OK
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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
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Residual Analysis – First City Real Estate
This is the Residual Plot for Square Feet
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Residual Analysis – First City Real Estate
While Excel will not automatically generate a histogram of the standardized residuals , one can be created.
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Residual Analysis – First City Real Estate
Define Bin values for the Histogram
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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
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Residual Analysis – First City Real Estate