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.
How predictions are made with regression analysis using the method of least squares to minimize errors in drawing a line of best fit.
How to test regression models for linearity and whether the equation is effective in fitting the data.
The nonparametric measures of association and the alternatives they offer when key assumptions and requirements for parametric techniques cannot be met.
