This chapter addresses statistical techniques that can be used to determine whether observed differences are likely to be real differences or whether they are likely attributable to sampling error. | Chapter Fourteen 14-1 More Powerful Statistical Methods Statistical Procedures 14-2 Key Terms & Definitions Correlation Analysis Key Concepts Correlation Analysis: Analysis of the degree to which changes in one variable are associated with changes in another. Pearson’s product–moment correlation: A correlation analysis technique for use with metric data. 14-3 Key Terms & Definitions Correlation Analysis Key Concepts 14-4 Key Terms & Definitions R2 –measure of the strength of the linear relationship between X and Y Coefficient of correlation R,- the degree of association between X and Y =square root of the coefficient of determination with the appropriate sign (+ or −). R can range from −1 (perfect negative correlation) to +1 (perfect positive correlation) The closer R, is to ±1, the stronger the degree of association between X and Y If R is equal to zero, then there is no association between X and Y Coefficient of Determination: Measure of the percentage of the . | Chapter Fourteen 14-1 More Powerful Statistical Methods Statistical Procedures 14-2 Key Terms & Definitions Correlation Analysis Key Concepts Correlation Analysis: Analysis of the degree to which changes in one variable are associated with changes in another. Pearson’s product–moment correlation: A correlation analysis technique for use with metric data. 14-3 Key Terms & Definitions Correlation Analysis Key Concepts 14-4 Key Terms & Definitions R2 –measure of the strength of the linear relationship between X and Y Coefficient of correlation R,- the degree of association between X and Y =square root of the coefficient of determination with the appropriate sign (+ or −). R can range from −1 (perfect negative correlation) to +1 (perfect positive correlation) The closer R, is to ±1, the stronger the degree of association between X and Y If R is equal to zero, then there is no association between X and Y Coefficient of Determination: Measure of the percentage of the variation in the dependent variable explained by variations in the independent variables. Regression Coefficients: Estimates of the effect of individual independent variables on the dependent variable. Dummy Variables: In regression analysis, a way of representing two-group or dichotomous, nominally scaled independent variables by coding one group as 0 and the other as 1. 14-5 Key Terms & Definitions Regression Analysis Measurement Applications A procedure for predicting the level or magnitude of a (metric) dependent variable based on the levels of multiple independent variables. Regression Analysis 14-6 Key Terms & Definitions Regression Analysis 14-7 Key Terms & Definitions Application of Regression Analysis 14-8 Key Terms & Definitions The professor might want to give some short examples of each one of these. Potential Use and Interpretation Problems Collinearity: Correlation of independent variables with each other, which can bias estimates of regression coefficients. .
