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Transcript
```Guide to Using Minitab 14 For Basic
Statistical Applications
To Accompany
Approach, 8th Ed.
Chapter 15:
Multiple Regression and Model Building
By
Groebner, Shannon, Fry, & Smith
Prentice-Hall Publishing Company
Chapter 15 Minitab
Examples




Multiple Regression
First City Real Estate
Multiple Regression – Variance Inflation Factor
First City Real Estate
Multiple Regression – Dummy Variable
First City Real Estate
Curvilinear Regression Prediction
Ashley Investment Services
More Examples
Chapter 15 Minitab
Examples (cont’d)



Second Order Model
Ashley Investment Services
Standard Stepwise Regression
Lomgmont Corporation
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 Minitab to build a multiple
regression model relating sales price to a set of
measurable variables.
Data file is First City.MTW
Multiple Regression – First City Real Estate
Open File First City.MTW
Multiple Regression – First City Real Estate
First click
on Stat,
then Basic
Statistics
and finally
on
Correlation.
Multiple Regression – First City Real Estate
Identify columns for
Variables. Click on OK
Multiple Regression – First City Real Estate
The Minitab
output shows
the correlation
(r = -0.073)
between Age
and Square
Feet.
Multiple Regression – First City Real Estate
The
correlation
between each
predictor and
Price is highly
significant.
Thus, each
predictor will
be inserted
into the
regression
model.
Multiple Regression – First City Real Estate
Click on Stat, then
Regression and then
Regression again.
Multiple Regression – First City Real Estate
Define the
columns
containing the
Response (Price)
and Predictor
Variables
Multiple Regression – First City Real Estate
The regression
coefficients, R2, S,
and sum of
squares are all
generated by the
regression
command.
Multiple Regression –
Dummy Variable
First City Real Estate
Issue: First City managers wish to improve the
model by adding a location variable.
Objective: Use Minitab to improve a regression
model by adding a dummy variable.
Data file is First City.MTW
Multiple Regression – Dummy Variable - First City
Open file First
City.MTW.
Multiple Regression – Dummy Variable - First City
Click on Stat then
Regression and then
Regression again.
Multiple Regression – Dummy Variable - First City
Select the columns
containing the
Response and
Predictor Variables.
Multiple Regression – Dummy Variable - First City
The output shows an
improved regression
model with the
variable, Area, included.
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 Minitab to determine whether the
relationship between the two measures is statistically
significant.
Data file is Ashley.MTW
Curvilinear Relationships – Ashley Investment Services
Open File Ashley.MTW
File contains values
for 20 Investment
Curvilinear Relationships – Ashley Investment Services
To develop
the scatter
plot first
click on
Graph
button then
select
Scatterplot
Curvilinear Relationships – Ashley Investment Services
Select
Simple
Curvilinear Relationships – Ashley Investment Services
Identify the columns
containing the
variables to be
graphed.
Curvilinear Relationships – Ashley Investment Services
Relationship may be
curvilinear – next, fit
linear to see model
results
Curvilinear Relationships – Ashley Investment Services
Click on Stat then Regression
and then Regression.
Curvilinear Relationships – Ashley Investment Services
Identify the columns
containing the X and
Y variables. Then
click OK.
Curvilinear Relationships – Ashley Investment Services
To find a nonlinear model,
click on Stat then Regression
and select Fitted Line Plot.
Curvilinear Relationships – Ashley Investment Services
Minitab
gives the
choice of
three
models,
select
Curvilinear Relationships – Ashley Investment Services
This gives
the
Regression
Line. The
Regression
Equation
and RSquare
value are
given.
Curvilinear Relationships – Ashley Investment Services
This gives
Regression
Equation
and Rsquare
value. The
R-Square
value is
larger than
that for
the linear
model.
Interactive Effects - Ashley
Investment Services
Issue: The director of personnel is trying to determine
whether there are interactive effects in the relationship
between employee burnout and time spent socializing
with co-workers.
Objective: Use Minitab to determine whether interactive
effects between the two measures are statistically
significant.
Data file is Ashley-2.MTW
Interactive Effects – Ashley Investment Services
Open File Ashley2.MTW
Interactive Effects – Ashley Investment Services
To simplify the next
few steps, modify the
names of Columns C2
and X2
Interactive Effects – Ashley Investment Services
Using the Calculator tab, set up
columns C4, C5 and C6 as:
Column C4 – Expression C2 * C2
Column C5 – Expression C2 * C1
Column C6 – Expression C4 * C3
Interactive Effects – Ashley Investment Services
Click on Stat then Regression and
then Regression.
Interactive Effects – Ashley Investment Services
Identify the columns
containing the X and
Y variables. Then
click OK.
Interactive Effects – Ashley Investment Services
Regression
Coefficients
Residual Analysis First City Real Estate
Issue: The company is interested in analyzing the
residuals of the regression model to determine whether
the assumptions are satisfied.
Objective: Use Minitab to analyze residuals from a
regression model.
Data file is First City-3.MTW
Residual Analysis – First City Real Estate
Open file First City-3.MTW
Residual Analysis – First City Real Estate
Click on Stat, then Regression
and then Regression again.
Residual Analysis – First City Real Estate
Identify the x and
y variables.
Residual Analysis – First City Real Estate
R-square = 96.9%
Residual Analysis – First City Real Estate
These are the
options using
the Graphs
button – Select
Residuals
versus fits.
Residual Analysis – First City Real Estate
Residual Plot
versus fitted y
values.
Residual Analysis – First City Real Estate
Select Histogram of
residuals
Residual Analysis – First City Real Estate
```
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