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. |