Chapter 9.4（课件）- 《统计学基础（英文版）》同步教学（人民大学版）

Chapter Correlation and Regression 9 1 Copyright 2019, 2015, 2012, Pearson Education, Inc. 1 Larson/Farber 6th ed Chapter 1 Chapter Outline 9.1 Correlation 9.2 Linear Regression 9.3 Measures of Regression and Prediction Intervals 9.4 Multiple Regression . 1 Copyright 2019, 2015, 2012, Pearson Education, Inc. Section 9.4 Multiple Regression . 1 Copyright 2019, 2015, 2012, Pearson Education, Inc. Section 9.4 Objectives How to use technology to find and interpret a multiple regression equation, the standard error of estimate and the coefficient of determination How to use a multiple regression equation to predict y-values . 1 Copyright 2019, 2015, 2012, Pearson Education, Inc. Multiple Regression Equation In many instances, a better prediction can be found for a dependent (response) variable by using more than one independent (explanatory) variable. For instance, a more accurate prediction for the carbon dioxide emissions discussed in previous sections might be made by considering the number of cars as well as the gross domestic product. . 1 Copyright 2019, 2015, 2012, Pearson Education, Inc. Multiple Regression Equation Multiple regression equation A multiple regression equation for independent variables x1, x2, x3, . . ., xk and a dependent variable y has the form ŷ = b + m1x1 + m2x2 + m3x3 + … + mkxk where ŷ is the predicted y-value for given xi values and b is the y-intercept. The y-intercept b is the value of ŷ when all xi are 0. Each coefficient mi is the amount of change in ŷ when the independent variable xi is changed by one unit and all other independent variables are held constant. . 1 Copyright 2019, 2015, 2012, Pearson Education, Inc. Example: Finding a Multiple Regression Equation A researcher wants to determine how employee salaries at a certain company are related to the length of employment, previous experience, and education. The researcher selects eight employees from the company and obtains the data shown on the next slide. Use Minitab to find