中南大学 multiple linear regression analysis.ppt

Chapter 15  Multiple linear regression Choice of independent variable Application Goal：construct the multiple linear regression model to assess the relationship between one dependant variable and a set of independent variables. Data：the dependant variable is quantitative data; the independent variables are all or most quantitative data. If there are some qualitative data or ranked data ,we must change them. Application ：explain and prediction. significance：Since the things are influenced by many facts, the change of dependent variable may influenced by many others independent variables. For example, the change of diabetes’ blood sugar may affected by many biochemical criterions such as insulin, glycosylated hemoglobin, total cholesterol of serum, triglyceride and so on. variable：one dependant variable, a set of independent . together m+1 。 Sample size：n Data form in Table 15-1 General model of the regression equation: 3、Hypothesis test and evaluation C．Standardization regression coefficient  Standardization variable is that subtract the mean of corresponding variable from original data, then divide by the standard deviation of variable. Attention : Generally, regression coefficient has unit, and to interpret the effect of each independent variable to dependent variable. It means when other independent variables keep steady, increases or decreases one unit that the average change of y. We can’t use each to compare the effect of to Standardization regression coefficient doesn’t have unit, and to compare the effect of each independent variable to dependent variable, the larger is, the larger effect of to § 2 choosing of independent variable  Case 15-2 Use entirely choose excellent method to choose independent variables in case 15-1 § 3 Application of Multiple Linear Regression and Attentions 1.1. Analysis of the related factors  For example, there are many factors that can affect hypertension, such a