Lecture 9 Simple Linear Regression 第九章 简单线性回归分析.ppt

Chapter 12
Simple Linear Regression
Business Statistics:
A First CourseFifth Edition
Chap 12-1
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc.
Learning Objectives
In this chapter, you learn:
How to use regression analysis to predict the value of a dependent variable based on an independent variable
The meaning of the regression coefficients b0 and b1
How to evaluate the assumptions of regression analysis and know what to do if the assumptions are violated
To make inferences about the slope and correlation coefficient
To estimate mean values and predict individual values
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Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc..
Correlation vs. Regression
A scatter plot can be used to show the relationship between two variables
Correlation analysis is used to measure the strength of the association (linear relationship) between two variables
Correlation is only concerned with strength of the relationship
No causal effect is implied with correlation
Scatter plots were first presented in Ch. 2
Correlation was first presented in Ch. 3
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Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc..
Introduction to Regression Analysis
Regression analysis is used to:
Predict the value of a dependent variable based on the value of at least one independent variable
Explain the impact of changes in an independent variable on the dependent variable
Dependent variable: the variable we wish to
predict or explain
Independent variable: the variable used to predict or explain the dependent variable
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Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc..
Simple Linear Regression Model
Only one independent variable, X
Relationship between X and Y is described by a linear function
Changes in Y are assumed to be related to changes in X
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Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc..
Types of Relationships
Y
X
Y
X
Y
Y
X
X
Linear relationships
Curvilinear relationships
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