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CHAPTER10
MULTIPLE REGRESSION
AND CORRELATION
CHAPTER OVERVIEW
This chapter provides extensions of the simple linear regression and bivariate
correlation models discussed in Chapter 9. The concepts and techniques
discussed here are useful when the researcher wishes to consider simultaneously
the relationships among more than two variables. Although the
concepts, computations, and interpretations associated with analysis of
multiple-variable data may seem complex, they are natural extensions of
material explored in previous chapters.
TOPICS
10.1 INTRODUCTION
10.2 THE MULTIPLE LINEAR REGRESSION MODEL
10.3 OBTAINING THE MULTIPLE REGRESSION EQUATION
10.4 EVALUATING THE MULTIPLE REGRESSION EQUATION
10.5 USING THE MULTIPLE REGRESSION EQUATION
10.6 THE MULTIPLE CORRELATION MODEL
10.7 SUMMARY
LEARNING OUTCOMES
After studying this chapter, the student will
1. understand how to include more than one independent variable in a regression
equation.
2. be able to obtain a multiple regression model and use it to make predictions.
3. be able to evaluate the multiple regression coefficients and the suitability of
the regression model.
4. understand how to calculate and interpret multiple, bivariate, and partial
correlation coefficients.
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