Learning Outcome Statements

1. Linear regression

a. distinguish between the dependent and independent variables in a linear regression;

2. Interpreting a regression coefficient

b. describe the assumptions underlying linear regression and interpret regression coefficients;

3. The standard error of estimate and the coefficient of determination

c. calculate and interpret the standard error of estimate, the coefficient of determination, and a confidence interval for a regression coefficient;

4. Confidence intervals for regression coefficients

c. calculate and interpret the standard error of estimate, the coefficient of determination, and a confidence interval for a regression coefficient;

5. Testing the significance of a regression coefficient

d. formulate a null and alternative hypothesis about a population value of a regression coefficient and determine the appropriate test statistic and whether the null hypothesis is rejected at a given level of significance;

6. The predicted value of the dependent variable

e. calculate the predicted value for the dependent variable, given an estimated regression model and a value for the independent variable;

f. calculate and interpret a confidence interval for the predicted value of the dependent variable;

7. Analysis of variance (ANOVA)

g. describe the use of analysis of variance (ANOVA) in regression analysis, interpret ANOVA results, and calculate and interpret the F-statistic;

8. Limitations of regression analysis

h. describe limitations of regression analysis.