Prep Packages for the CFA® Program offered by AnalystPrep (study notes, video lessons, question bank, mock exams, and much more):

Level I: https://analystprep.com/shop/cfaleve...

Level II: https://analystprep.com/shop/learnpr...

Levels I, II & III (Lifetime access): https://analystprep.com/shop/cfaunli...

Prep Packages for the FRM® Program:

FRM Part I & Part II (Lifetime access): https://analystprep.com/shop/unlimite...

Topic 1 – Quantitative Methods
Readings 2 – Multiple Regression
0:00 Introduction and Learning Outcome Statements
0:54 LOS: Formulate a multiple regression equation to describe the relation between a dependent variable and several independent variables and determine the statistical significance of each independent variable
3:24 LOS: Interpret estimated regression coefficients and their pvalues;
6:12 LOS: Formulate a null and an alternative hypothesis about the population value of a regression coefficient, calculate the value of the test statistic, and determine whether to reject the null hypothesis at a given level of significance;
11:57 LOS: Interpret the results of hypothesis tests of regression coefficients;
13:40 LOS: Calculate and interpret a predicted value for the dependent variable, given an estimated regression model and assumed values for the independent variables;
16:44 LOS: Explain the assumptions of a multiple regression model
17:45 LOS: Calculate and interpret the Fstatistic, and describe how it is used in regression analysis
23:15 LOS: Contrast and interpret the R2 and adjusted R2 in multiple regressions
27:47 LOS: Evaluate how well a regression model explains the dependent variable by analyzing the output of the regression equation and an ANOVA table;
32:15 LOS: Formulate and interpret a multiple regression equation by using dummy variables to represent qualitative factors and interpret the coefficients and regression results
39:12 LOS: Explain the types of heteroskedasticity and how heteroskedasticity and serial correlation affect statistical inference;
43:50 LOS: Describe multicollinearity and explain its causes and effects in regression analysis;
47:22 LOS: Describe how model misspecification affects the results of regression analysis and describe how to avoid common forms of misspecification;
48:59 LOS: Describe models with qualitative dependent variables
50:41 LOS: Evaluate and interpret a multiple regression model and its results