tailieunhanh - Lecture Business research methods (11/e): Chapter 18 - Donald R. Cooper, Pamela S. Schindler

This chapter explains the use of several techniques including correlation analysis and regression analysis. After reading this chapter, you should 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;. | Chapter 18 Measures of Association McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved. This chapter explains the use of several techniques including correlation analysis and regression analysis. 18- 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. 18- 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. 18- Invalid Assumptions “The invalid assumption that correlation implies cause is . | Chapter 18 Measures of Association McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved. This chapter explains the use of several techniques including correlation analysis and regression analysis. 18- 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. 18- 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. 18- Invalid Assumptions “The invalid assumption that correlation implies cause is probably among the two or three most serious and common errors of human reasoning.” Stephen Jay Gould paleontologist and science writer 18- PulsePoint: Research Revelation 25 The percent of students using a credit card for college costs due to convenience. See the text Instructors Manual (downloadable from the text website) for ideas for using this research-generated statistic. 18- 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 Exhibit 18-1 in the text presents a list of commonly .