Chapter Eighteen

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Chapter Eighteen
Chapter 18
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Figure 18.1 Relationship to the Previous
Chapters The Marketing Research Process
Figure 18.1 Relationship of Correlation and
Regression to the Previous Chapters and the
Marketing Research Process
Focus of This Chapter
Relationship to Previous Chapters
Relationship to Marketing Research Process

• Correlation
• Regression

• Analytical Framework and Models
  (Chapter 2)
• Data Analysis Strategy (Chapter 15)
• General Procedure of Hypothesis Testing
  (Chapter 16)
• Hypothesis Testing Related to Differences
  (Chapter 17)

Problem Definition
Approach to Problem
Research Design
Field Work
Data Preparation and Analysis
Report-Preparation and Presentation
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Figure 18.2 Correlation and Regression An
Overview
Figure 18.2 Correlation and Regression An
Overview
Opening Vignette
Product Moment Correlation
Fig 18.3-18.4
Table 18.1
Regression Analysis
Focus on Elrick Lavidge
Internet Applications
Bivariate Regression
Figs 18.5-18.7
Table 18.2
Multiple Regression
Table 18.3
Application to Contemporary Issues
TQM
International
Technology
Ethics
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Figure 18.3 Plot of Attitude With Duration of
Car Ownership
Figure 18.3 Plot of Attitude With Duration of
Car Ownership
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Figure 18.4 A Nonlinear Relationship for Which r
0
Figure 18.4 A Nonlinear Relationship for Which r
0
.
.
6
.
.
5
4
.
.
3
2
.
1
0
-3
-2
-1
0
1
2
3
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Figure 18.5 Conducting Bivariate Regression
Analysis
Figure 18.5 Conducting Bivariate Regression
Analysis
Opening Vignette
Scatter Diagram
General Model
Focus on Elrick Lavidge
Internet Applications
Estimation of Parameters
Standardized Regression Coefficient
Application to Contemporary Issues
TQM
International
Technology
Ethics
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Figure 18.5 Conducting Bivariate Regression
Analysis (continued)
Figure 18.5 Conducting Bivariate Regression
Analysis (continued)
Opening Vignette
Significance Testing
Strength and Significance of Association
Focus on Elrick Lavidge
Internet Applications
Prediction Accuracy
Examination of Residuals
Application to Contemporary Issues
TQM
International
Technology
Ethics
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Figure 18.6 Bivariate Regression
Figure 18.6 Bivariate Regression
Y
b0 b1 X
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Figure 18.7 Decomposition of the Total Variation
In Bivariate Regression
Figure 18.7 Decomposition of the Total Variation
In Bivariate Regression


Residual variation, SS RES
Total variation, SSY
Y

Explained variation, SS REG
Y
X
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Figure 18.8 Other Computer Programs for
Correlations
Figure 18.8 Other Computer Programs for
Correlations
SAS CORR produces metric and nonmetric
correlations between variables, including
Pearsons product moment correlation. MINITAB Corr
elation can be computed using STATgtBASICSTATISTICS
gt CORRELATION function. It calculates Pearsons
product moment using all the columns. EXCEL Correl
ations can be determined in EXCEL by using the
TOOLSgtDATA ANALYSISgtCORRELATION function. Use
the Correlation Worksheet Function when a
correlation coefficient for two cell ranges is
needed.
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Figure 18.9 Other Computer Programs for Regression
Figure 18.8 Other Computer Programs for
Regression
SAS REG is a general purpose regression procedure
that fits bivariate and multiple regression
models using the least-squares procedures. All
the associated statistics are computed, and
residuals can be plotted. MINITAB Regression
analysis under the STATSgtREGRESSIOIN function can
perform simple and multiple analysis. The output
includes a linear regression equation, table of
coefficients R square, R squared adjusted,
analysis of variance table, a table of fits and
residuals that provide unusual observations.
Other available features include fitted line
plot, and residual plots. EXCEL Regression can be
assessed from the TOOLSgtDATA ANALYSIS menu.
Depending on the features selected, the output
can consist of a summary output table, including
an ANOVA table, a standard error of y estimate,
coefficients, standard error of coefficients, R2
values, and the number of observations. In
addition, the function computes a residual output
table, a residual plot, a line fit plot, normal
probability plot, and a two-column probability
data output table.
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Table 18.1 Explaining Attitude Toward Sports Cars
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Table 18.2 Bivariate Regression
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Table 18.3 Multiple Regression