英文商务统计学课件第十三章_Ch13.pptxVIP

Chapter 13Multiple RegressionBusiness Statistics: A First CourseFifth EditionChap 13-1 Learning Objectives2In this chapter, you learn:How to develop a multiple regression modelHow to interpret the regression coefficients How to determine which independent variables to include in the regression model How to determine which independent variables are more important in predicting a dependent variableHow to use categorical variables in a regression model The Multiple RegressionModelIdea: Examine the linear relationship between1 dependent (Y) 2 or more independent variables (Xi)Multiple Regression Model with k Independent Variables:Y-interceptPopulation slopes Random Error3 Multiple Regression EquationEstimated(or predicted) value of YEstimated slope coefficientsThe coefficients of the multiple regression model are estimated using sample dataMultiple regression equation with k independent variables:Estimated interceptIn this chapter we will use Excel or Minitab to obtain the regression slope coefficients and other regression summary measures.4 X15X2Slope for variable X1Slope for variable X2Multiple Regression Equation(continued)Two variable modelY Example:2 Independent Variables A distributor of frozen dessert pies wants to evaluate factors thought to influence demandDependent variable:Independent variables:Pie sales (units per week)Price (in $) Advertising ($100’s)Data are collected for 15 weeks6 Pie Sales ExampleWeekPie SalesPrice ($)Advertising ($100s)13505.503.324607.503.333508.003.044308.004.553506.803.063807.504.074304.503.084706.403.794507.003.5104905.004.0113407.203.5123007.903.2134405.904.0144505.003.5153007.002.7Multiple regression equation:Sales = b0 + b1 (Price)+ b2 (Advertising)7 Excel Multiple Regression OutputRegression StatisticsMultiple R0.72213R Square0.52148Adjusted R Square0.44172Standard Error47.46341Observations15ANOVAdf SS MS F Significance FRegression2294600136.538610.01201Residual1227033.3062252.776Total1456493.333CoefficientsStandard E