chapter17.ppt 386KB Dec 31 1997 01:39:24 PM
Chapter XVII
Correlation
and
Regression
Chapter Outline
1) Overview
2) ProductMoment Correlation
3) Partial Correlation
4) Nonmetric Correlation
5) Regression Analysis
6) Bivariate Regression
7) Statistics Associated with Bivariate Regression Analysis
8) Conducting Bivariate Regression Analysis
i. Scatter Diagram
iii. Estimation of Parameters
iv. Standardized Regression Coefficient
v. Significance Testing
vi. Strength and Significance of Association
vii. Prediction Accuracy
viii. Assumptions
9) Multiple Regression
10) Statistics Associated with Multiple Regression
11) Conducting Multiple Regression
i. Partial Regression Coefficients
ii. Strength of Association
iii. Significance Testing
iv. Examination of Residuals
12) Stepwise Regression
13) Multicolinearity
14) Relative Importance of Predictors
15) Cross Validation
16) Regression with Dummy Variables
17) Analysis of Variance and Covariance with Regression
18) Internet and Computer Applications
19) Focus on Burke
20) Summary
21) Key Terms and Concepts
22) Acronyms
Table 17.1
Explaining Attitude Toward the
City of Residence
Respondent
No
Attitude
Toward the
City
Duration of
Residence
Importance
Attached to
Weather
1
6
10
3
2
9
12
11
3
8
12
4
4
3
4
1
5
10
12
11
6
4
6
1
7
5
8
7
8
2
2
4
9
11
18
8
10
9
9
10
11
10
17
8
12
2
2
5
Figure 17.1
A Nonlinear Relationship
for Which r = 0
Y6
5
4
3
2
1
0
3
2
1
0
1
2
3
X
Conducting Bivariate Regression Analysis
Fig. 17.2
Plot the Scatter Diagram
Formulate the General Model
Estimate the Parameters
Estimate Standardized Regression Coefficients
Test for Significance
Determine the Strength and Significance of Association
Check Prediction Accuracy
Examine the Residuals
CrossValidate the Model
Figure 17.3
Plot of Attitude with Duration
Attitude
9
6
3
2.25
4.5
6.75 9 11.25 13.5 15.75 18
Duration of Residence
Bivariate Regression
Figure 17.4
Y
YJ
eJ
eJ
YJ
X1
X2
X3
X4
X5
X
Bivariate Regression
Table 17.2
Multiple R
R2
Adjusted R2
Standard Error
.93608
.87624
.86387
1.22329
ANALYSIS OF VARIANCE
df
Sum of Squares
Mean Square
Regression
1
Residual
10
F =
70.80266
Variable
Duration
(Constant)
105.95222
105.95222
14.96444
1.49644
Significance of F = .0000
VARIABLES IN THE EQUATION
b
SEb
Beta (ß) T
Significance
of T
.58972 .07008 .93608 8.414
.0000
1.07932 .74335
1.452
.1772
Figure 17.5
Decomposition of the Total
Variation in Bivariate Regression
Y
Residual Variation
SSres
Explained Variation
SSreg
Y
tal on
o
T ati
ri y
a
V SS
X1
X2
X3
X4
X5
X
Multiple Regression
Table 17.3
Multiple R
R2
Adjusted R2
Standard Error
.97210
.94498
.93276
.85974
ANALYSIS OF VARIANCE
df
Sum of Squares
Mean Square
Regression
2
Residual
9
F =
77.29364
Variable
Importance
Duration
(Constant)
114.26425
57.13213
6.65241
.73916
Significance of F = .0000
VARIABLES IN THE EQUATION
b
SE b
Beta (ß) T
Significance
of T
.28865 .08608 .31382 3.353
.0085
.48108 .05895 .76363 8.160
.0000
.33732 .56736
.595
.5668
Residuals
Residual Plot Indicating that Variance
is Not Constant
Figure 17.6
Predicted Y Values
Residual Plot Indicating a Linear
Relationship Between Residuals and Time
Residuals
Figure 17.7
Time
Plot of Residuals Indicating that a
Fitted Model is Appropriate
Residuals
Figure 17.8
Predicted Y Values
R.I.P. 17.1
Frequent Fliers: Fly from
the Clouds to the Clear
Airline Companies in Asia were facing uncertainty and tough competition from U.S.
carriers for a long time. Asian Airlines, hit by global recession and preemptive competitive
deals, awakened to the realization of banding together to increase air patronage. Secondary
data revealed that among the important factors leading to airline selection by consumers
were price, ontime schedules, destinations, deals available, kitchen and food service, on
flight service, etc. Asian airlines offered these services at par if not better. In fact, research
showed that inflight and kitchen services may have been even better. So, why were they
feeling the competitive pressure? Qualitative research in the form of focus groups revealed
that the frequent flier program was a critical factor for a broad segment in general and the
business segment in particular. A survey of international passengers was conducted and
multiple regression analyses was used to analyze the data. The likelihood of flying and
other choice measures served as the dependent variable and the set of service factors,
including the frequent flier program, were the independent variables. The results indicated
that frequent flier program, indeed, had a significant effect on the choice of an airline.
Based on these findings, Cathay Pacific, Singapore International Airlines, Thai Airways
International, and Malaysian Airline systems introduced a cooperative frequent flier
program called Asia Plus available to all travelers. The program was the first time the
Asian carriers offered free travel in return for regular patronage. A multimillion dollar
marketing and advertising campaign was started in 1993 to promote Asia Plus. Frequent
fliers, thus, flew from the clouds to the clear and the Asian airlines experienced increased
passenger traffic.
R.I.P. 17.2
Reasons for Researchers
Regressing to Unethical Behavior
Marketing research has been targeted as a major source of ethical problems within
the discipline of marketing. In particular, marketing research has been charged
with engaging in: deception, conflict of interest, violation of anonymity, invasion
of privacy, data falsifications, dissemination of faulty research findings, and the
use of research as a guise to sell merchandise. It has been speculated that when a
researcher chooses to participate in unethical activities, that decision may be
influenced by organizational factors. Therefore, a study using multiple regression
analysis was designed to examine organizational factors as determinants of the
incidence of unethical research practices. Six organizational variables were used
as the independent variables, namely: extent of ethical problems within the
organization, top management actions on ethics, code of ethics, organizational
rank, industry category, and organizational role. The respondent's evaluation of
the incidence of unethical research practices served as the dependent variable.
Regression analysis of the data suggested that four of the six organization variables
influenced the extent of unethical research practice: extent of ethical problems
within the organization, top management actions on ethics, organizational role, and
industry category.
Correlation
and
Regression
Chapter Outline
1) Overview
2) ProductMoment Correlation
3) Partial Correlation
4) Nonmetric Correlation
5) Regression Analysis
6) Bivariate Regression
7) Statistics Associated with Bivariate Regression Analysis
8) Conducting Bivariate Regression Analysis
i. Scatter Diagram
iii. Estimation of Parameters
iv. Standardized Regression Coefficient
v. Significance Testing
vi. Strength and Significance of Association
vii. Prediction Accuracy
viii. Assumptions
9) Multiple Regression
10) Statistics Associated with Multiple Regression
11) Conducting Multiple Regression
i. Partial Regression Coefficients
ii. Strength of Association
iii. Significance Testing
iv. Examination of Residuals
12) Stepwise Regression
13) Multicolinearity
14) Relative Importance of Predictors
15) Cross Validation
16) Regression with Dummy Variables
17) Analysis of Variance and Covariance with Regression
18) Internet and Computer Applications
19) Focus on Burke
20) Summary
21) Key Terms and Concepts
22) Acronyms
Table 17.1
Explaining Attitude Toward the
City of Residence
Respondent
No
Attitude
Toward the
City
Duration of
Residence
Importance
Attached to
Weather
1
6
10
3
2
9
12
11
3
8
12
4
4
3
4
1
5
10
12
11
6
4
6
1
7
5
8
7
8
2
2
4
9
11
18
8
10
9
9
10
11
10
17
8
12
2
2
5
Figure 17.1
A Nonlinear Relationship
for Which r = 0
Y6
5
4
3
2
1
0
3
2
1
0
1
2
3
X
Conducting Bivariate Regression Analysis
Fig. 17.2
Plot the Scatter Diagram
Formulate the General Model
Estimate the Parameters
Estimate Standardized Regression Coefficients
Test for Significance
Determine the Strength and Significance of Association
Check Prediction Accuracy
Examine the Residuals
CrossValidate the Model
Figure 17.3
Plot of Attitude with Duration
Attitude
9
6
3
2.25
4.5
6.75 9 11.25 13.5 15.75 18
Duration of Residence
Bivariate Regression
Figure 17.4
Y
YJ
eJ
eJ
YJ
X1
X2
X3
X4
X5
X
Bivariate Regression
Table 17.2
Multiple R
R2
Adjusted R2
Standard Error
.93608
.87624
.86387
1.22329
ANALYSIS OF VARIANCE
df
Sum of Squares
Mean Square
Regression
1
Residual
10
F =
70.80266
Variable
Duration
(Constant)
105.95222
105.95222
14.96444
1.49644
Significance of F = .0000
VARIABLES IN THE EQUATION
b
SEb
Beta (ß) T
Significance
of T
.58972 .07008 .93608 8.414
.0000
1.07932 .74335
1.452
.1772
Figure 17.5
Decomposition of the Total
Variation in Bivariate Regression
Y
Residual Variation
SSres
Explained Variation
SSreg
Y
tal on
o
T ati
ri y
a
V SS
X1
X2
X3
X4
X5
X
Multiple Regression
Table 17.3
Multiple R
R2
Adjusted R2
Standard Error
.97210
.94498
.93276
.85974
ANALYSIS OF VARIANCE
df
Sum of Squares
Mean Square
Regression
2
Residual
9
F =
77.29364
Variable
Importance
Duration
(Constant)
114.26425
57.13213
6.65241
.73916
Significance of F = .0000
VARIABLES IN THE EQUATION
b
SE b
Beta (ß) T
Significance
of T
.28865 .08608 .31382 3.353
.0085
.48108 .05895 .76363 8.160
.0000
.33732 .56736
.595
.5668
Residuals
Residual Plot Indicating that Variance
is Not Constant
Figure 17.6
Predicted Y Values
Residual Plot Indicating a Linear
Relationship Between Residuals and Time
Residuals
Figure 17.7
Time
Plot of Residuals Indicating that a
Fitted Model is Appropriate
Residuals
Figure 17.8
Predicted Y Values
R.I.P. 17.1
Frequent Fliers: Fly from
the Clouds to the Clear
Airline Companies in Asia were facing uncertainty and tough competition from U.S.
carriers for a long time. Asian Airlines, hit by global recession and preemptive competitive
deals, awakened to the realization of banding together to increase air patronage. Secondary
data revealed that among the important factors leading to airline selection by consumers
were price, ontime schedules, destinations, deals available, kitchen and food service, on
flight service, etc. Asian airlines offered these services at par if not better. In fact, research
showed that inflight and kitchen services may have been even better. So, why were they
feeling the competitive pressure? Qualitative research in the form of focus groups revealed
that the frequent flier program was a critical factor for a broad segment in general and the
business segment in particular. A survey of international passengers was conducted and
multiple regression analyses was used to analyze the data. The likelihood of flying and
other choice measures served as the dependent variable and the set of service factors,
including the frequent flier program, were the independent variables. The results indicated
that frequent flier program, indeed, had a significant effect on the choice of an airline.
Based on these findings, Cathay Pacific, Singapore International Airlines, Thai Airways
International, and Malaysian Airline systems introduced a cooperative frequent flier
program called Asia Plus available to all travelers. The program was the first time the
Asian carriers offered free travel in return for regular patronage. A multimillion dollar
marketing and advertising campaign was started in 1993 to promote Asia Plus. Frequent
fliers, thus, flew from the clouds to the clear and the Asian airlines experienced increased
passenger traffic.
R.I.P. 17.2
Reasons for Researchers
Regressing to Unethical Behavior
Marketing research has been targeted as a major source of ethical problems within
the discipline of marketing. In particular, marketing research has been charged
with engaging in: deception, conflict of interest, violation of anonymity, invasion
of privacy, data falsifications, dissemination of faulty research findings, and the
use of research as a guise to sell merchandise. It has been speculated that when a
researcher chooses to participate in unethical activities, that decision may be
influenced by organizational factors. Therefore, a study using multiple regression
analysis was designed to examine organizational factors as determinants of the
incidence of unethical research practices. Six organizational variables were used
as the independent variables, namely: extent of ethical problems within the
organization, top management actions on ethics, code of ethics, organizational
rank, industry category, and organizational role. The respondent's evaluation of
the incidence of unethical research practices served as the dependent variable.
Regression analysis of the data suggested that four of the six organization variables
influenced the extent of unethical research practice: extent of ethical problems
within the organization, top management actions on ethics, organizational role, and
industry category.