13 © 2004 by The McGrawHill Companies, Inc. All rights reserved. 13 2. 13 2. When you have completed this chapter, you will be able to: 1. Identify a relationship between variables on a . scatter diagram. 2. Measure and interpret a degree of relationship . by a coefficient of correlation. 3. Conduct a test of hypothesis about the . coefficient of correlation in a population 4. Identify the roles of dependent and independent . variables, the concept of regression, and its . distinction from the concept of © 2004 by The McGrawHill Companies, Inc. All rights reserved. 13 3. 13 3 5. Measure and interpret the strength of relationship . between two variables through a regression line . and the technique of least squares 6. Conduct analysis of variance and calculate . coefficient of determination 7. Conduct a test of hypothesis for a regression . model and each coefficient of regression. 8. Estimate confidence and prediction intervalsCopyright © 2004 by The McGrawHill Companies, Inc. All rights reserved. Terminology. 13 4. Correlation Analysis. is a group of statistical techniques used to measure the . strength of the association between two variables Scatter Diagram . is a chart that portrays the relationship . between the two variables. . Dependent Variable. is the variable being predicted or estimated. Independent Variable. provides the basis for estimation. . It is the predictor © 2004 by The McGrawHill Companies, Inc. All rights reserved. The Coefficient of Correlation rr. 13 5. The Coefficient of Correlation . Is a measure of strength of the relationship . between two variables . It requires interval or ratioscaled data. It can range from to . Values of or indicate perfect . and strong correlation. Values close to indicate weak correlation Negative values indicate an inverse relationship . and positive values indicate a direct © 2004 by The McGrawHill Companies, Inc. All rights reserved. Perfect Negative. Perfect Negative Correlation. Correlation. 13 6. 10. 9. 8. 7. 6. Y 5. 4.
