1. Chapter XVII CorrelationandRegression

2. Chapter Outline Chapter Outline 1) Overview 2) Product-Moment 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 i. Scatter Diagram ii. Bivariate Regression Model ii. Bivariate Regression Model

3. iii. Estimation of Parameters iii. Estimation of Parameters iv. Standardized Regression Coefficient iv. Standardized Regression Coefficient v. Significance Testing v. Significance Testing vi. Strength and Significance of Association vi. Strength and Significance of Association vii. Prediction Accuracy vii. Prediction Accuracy viii. Assumptions viii. Assumptions 9) Multiple Regression 10) Statistics Associated with Multiple Regression 11) Conducting Multiple Regression i. Partial Regression Coefficients i. Partial Regression Coefficients ii. Strength of Association ii. Strength of Association iii. Significance Testing iii. Significance Testing iv. Examination of Residuals iv. Examination of Residuals

4. 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

5. Table 17.1 Explaining Attitude Toward the City of Residence City of Residence

6. A Nonlinear Relationship for Which r = 0 Figure 17.1 -2 0 2 1 3 4 3 1 2 0 5 Y6Y6 -3 X

7. Conducting Bivariate Regression Analysis Fig. 17.2 Plot the Scatter DiagramFormulate the General ModelEstimate the ParametersEstimate Standardized Regression CoefficientsTest for SignificanceDetermine the Strength and Significance of AssociationCheck Prediction AccuracyExamine the ResidualsCross-Validate the Model

8. Plot of Attitude with Duration Figure 17.3 4.52.25 6.75 11.25 9 13.5 9 3 6 15.7518 Duration of Residence Attitude

9. Bivariate Regression Figure 17.4 X2X1X3 X5 X4 YJYJYJYJ eJeJ YJYJYJYJ X Y

10. Table 17.2 Multiple R.93608 R 2.87624 Adjusted R 2.86387 Standard Error1.22329 ANALYSIS OF VARIANCE dfSum of SquaresMean Square Regression1105.95222105.95222 Residual1014.964441.49644 F =70.80266Significance of F =.0000 VARIABLES IN THE EQUATION VariablebSE b Beta (ß) TSignificance of T Duration.58972.07008.936088.414.0000 (Constant)1.07932.743351.452.1772 Bivariate Regression

11. Decomposition of the Total Variation in Bivariate Regression Figure 17.5 X2X1X3 X5 X4 Y X TotalVariation SS y Residual Variation SS res Explained Variation SS reg Y

12. Multiple R.97210 R 2.94498 Adjusted R 2.93276 Standard Error.85974 ANALYSIS OF VARIANCE dfSum of SquaresMean Square Regression2114.2642557.13213 Residual96.65241.73916 F =77.29364Significance of F =.0000 VARIABLES IN THE EQUATION VariablebSE bBeta (ß) TSignificance of T Importance.28865.08608.313823.353.0085 Duration.48108.05895.763638.160.0000 (Constant).33732.56736.595.5668 Table 17.3 Multiple Regression

13. Residual Plot Indicating that Variance is Not Constant Figure 17.6 Predicted Y Values Residuals

14. Residual Plot Indicating a Linear Relationship Between Residuals and Time Figure 17.7 Time Residuals

15. Plot of Residuals Indicating that a Fitted Model is Appropriate Figure 17.8 Predicted Y Values Residuals

16. 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 pre-emptive 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, on-time 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 in-flight 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. 17.1 Frequent Fliers: Fly from the Clouds to the Clear

17. 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. R.I.P. 17.2 Reasons for Researchers Regressing to Unethical Behavior