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Lecture Business research methods (12/e): Chapter 18 - Donald R. Cooper, Pamela S. Schindler

Chapter 18 - Measures of association. After studying this chapter you will be able to understand: How correlation analysis may be applied to study relationships between two or more variables; the uses, requirements, and interpretation of the product moment correlation coefficient; how predictions are made with regression analysis using the method of least squares to minimize errors in drawing a line of best fit;. | Measures of Association Chapter 18 1 Learning Objectives Understand . . . How correlation analysis may be applied to study relationships between two or more variables The uses, requirements, and interpretation of the product moment correlation coefficient. How predictions are made with regression analysis using the method of least squares to minimize errors in drawing a line of best fit. 2 Learning Objectives Understand . . . How to test regression models for linearity and whether the equation is effective in fitting the data. Nonparametric measures of association and the alternatives they offer when key assumptions and requirements for parametric techniques cannot be met. 3 Pull Quote “Consumer behavior with digital editions of magazines is very much like their behavior with print editions of magazines, and very much unlike their behavior with websites. Readers typically swipe through tablet editions from front to back, for example, the same way they work their way through print . | Measures of Association Chapter 18 1 Learning Objectives Understand . . . How correlation analysis may be applied to study relationships between two or more variables The uses, requirements, and interpretation of the product moment correlation coefficient. How predictions are made with regression analysis using the method of least squares to minimize errors in drawing a line of best fit. 2 Learning Objectives Understand . . . How to test regression models for linearity and whether the equation is effective in fitting the data. Nonparametric measures of association and the alternatives they offer when key assumptions and requirements for parametric techniques cannot be met. 3 Pull Quote “Consumer behavior with digital editions of magazines is very much like their behavior with print editions of magazines, and very much unlike their behavior with websites. Readers typically swipe through tablet editions from front to back, for example, the same way they work their way through print editions. They browse—taking in ads as they go—instead of jumping directly to specific articles the way web surfers do.” Scott McDonald, senior vice-president for research and insights, Conde Nast Measures of Association: Interval/Ratio Data Pearson correlation coefficient For continuous linearly related variables Correlation ratio (eta) For nonlinear data or relating a main effect to a continuous dependent variable Biserial One continuous and one dichotomous variable with an underlying normal distribution Partial correlation Three variables; relating two with the third’s effect taken out Multiple correlation Three variables; relating one variable with two others Bivariate linear regression Predicting one variable from another’s scores 5 Measures of Association: Ordinal Data Gamma Based on concordant-discordant pairs; proportional reduction in error (PRE) interpretation Kendall’s tau b P-Q based; adjustment for tied ranks Kendall’s tau c P-Q based; adjustment for table dimensions .