### Seeing is believing!

Before you order, simply sign up for a free user account and in seconds you'll be experiencing the best in CFA exam preparation.

##### Learning Outcome Statements
 1. Simple Linear Regressiona. describe a simple linear regression model and the roles of the dependent and independent variables in the model; 2. Estimating the Parameters of a Simple Linear Regressionb. describe the least squares criterion, how it is used to estimate regression coefficients, and their interpretation; 3. Assumptions of the Simple Linear Regression Modelc. explain the assumptions underlying the simple linear regression model, and describe how residuals and residual plots indicate if these assumptions may have been violated; 4. Analysis of Varianced. calculate and interpret the coefficient of determination and the F-statistic in a simple linear regression; e. describe the use of analysis of variance (ANOVA) in regression analysis, interpret ANOVA results, and calculate and interpret the standard error of estimate in a simple linear regression; 5. Hypothesis Testing of Linear Regression Coefficientsf. formulate a null and an alternative hypothesis about a population value of a regression coefficient, and determine whether the null hypothesis is rejected at a given level of significance; 6. Prediction Using Simple Linear Regression and Prediction Intervalsg. calculate and interpret the predicted value for the dependent variable, and a prediction interval for it, given an estimated linear regression model and a value for the independent variable; 7. Functional Forms for Simple Linear Regressionh. describe different functional forms of simple linear regressions.
I am happy to say that I passed! Your study notes certainly helped prepare me for what was the most difficult exam I had ever taken.