文档介绍：Chapter 16 Multiple Regression and Correlation
to pany
Introduction to Business Statistics
fourth edition, by Ronald M. Weiers
Presentation by Priscilla Chaffe-Stengel
Donald N. Stengel
© 2002 The Wadsworth Group
Chapter 16 Learning Objectives
Obtain and interpret the multiple regression equation
Make estimates using the regression model:
Point value of the dependent variable, y
Intervals:
Confidence interval for the conditional mean of y
Prediction interval for an individual y observation
Conduct and interpret hypothesis tests on the
Coefficient of multiple determination
Partial regression coefficients
© 2002 The Wadsworth Group
Chapter 16 - Key Terms
Partial regression coefficients
Multiple standard error of the estimate
Conditional mean of y
Individual y observation
Coefficient of multiple determination
Coefficient of partial determination
Global F-test
Standard deviation of bi
© 2002 The Wadsworth Group
The Multiple Regression Model
Probabilistic Model
yi = b0 + b1x1i + b2x2i + ... + bkxki + ei
where yi = a value of the dependent variable, y
b0 = the y-intercept
x1i, x2i, ... , xki = individual values of the independent variables, x1, x2, ... , xk
b1, b2 ,... , bk = the partial regression coefficients for the independent variables, x1, x2, ... , xk
ei = random error, the residual
© 2002 The Wadsworth Group
The Multiple Regression Model
Sample Regression Equation
= b0 + b1x1i + b2x2i + ... + bkxki
where = the predicted value of the dependent variable, y, given the values of x1, x2, ... , xk
b0 = the y-intercept
x1i, x2i, ... , xki = individual values of the independent variables, x1, x2, ... , xk
b1, b2, ... , bk = the partial regression coefficients for the independent variables, x1, x2, ... , xk
© 2002 The Wadsworth Group
The Amount of Scatter in the Data
The multiple standard error of the estimate
where yi = each observed value of y in the data set
= the value of y that would have been estimated from the regression equation