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##### Learning Outcome Statements
 1. Linear regressiona. distinguish between the dependent and independent variables in a linear regression; 2. Interpreting a regression coefficientb. describe the assumptions underlying linear regression and interpret regression coefficients; 3. The standard error of estimate and the coefficient of determinationc. 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 coefficientsc. 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 coefficientd. 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 variablee. 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 analysish. describe limitations of regression analysis.
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