Chapter 9 presents multiple regression and issues in regression analysis. This chapter includes contents: Multiple regression, multiple regression assumptions, multiple regression predicted values, multiple regression: anova, indicator variables,. Inviting you refer. | Multiple regression and issues in regression analysis At the outset of this lecture, point out that the results contained in the tables were determined using a statistical package within Excel, while the presentation shows various variables/estimates rounded off to four decimal places for the sake of clarity. In several places, this will lead to the full 32-bit precision result differing slightly from the value you will get if you replicate the indicated formula calculations. 1 Multiple regression With multiple regression, we can analyze the association between more than one independent variable and our dependent variable. Returning to our analysis of the determinants of loan rates, we also believe that the number of lines of credit the client currently employs is related to the loan rate charged. Accordingly, we model a multiple linear regression of the relationship: General form Specific form where DTI is the debt-to-income ratio and Open lines is the number of existing lines of | Multiple regression and issues in regression analysis At the outset of this lecture, point out that the results contained in the tables were determined using a statistical package within Excel, while the presentation shows various variables/estimates rounded off to four decimal places for the sake of clarity. In several places, this will lead to the full 32-bit precision result differing slightly from the value you will get if you replicate the indicated formula calculations. 1 Multiple regression With multiple regression, we can analyze the association between more than one independent variable and our dependent variable. Returning to our analysis of the determinants of loan rates, we also believe that the number of lines of credit the client currently employs is related to the loan rate charged. Accordingly, we model a multiple linear regression of the relationship: General form Specific form where DTI is the debt-to-income ratio and Open lines is the number of existing lines of credit the client already possesses. 2 LOS: Formulate a multiple regression equation to describe the relationship between a dependent variable and several independent variables, determine the statistical significance of each independent variable, and interpret the estimated coefficients. Pages 325–326 It is rare to run a regression with only a single independent variable, although less so in investments than in corporate finance. Accordingly, the issues surrounding multiple independent variables are particularly important, as are the specialized topics in this chapter. At the outset of this lecture, point out that the results contained in the tables were determined using a statistical package within Excel, while the presentation shows various variables/estimates rounded off to four decimal places for the sake of clarity. In several places, this will lead to the full 32-bit precision result differing slightly from the value you will get if you replicate the indicated formula .
