Encyclopedia of Operations Research and Management Science

2001 Edition
| Editors: Saul I. Gass, Carl M. Harris

Regression analysis

  • Irwin Greenberg
Reference work entry
DOI: https://doi.org/10.1007/1-4020-0611-X_871
  • 22 Downloads

INTRODUCTION

In almost all fields of study, the researcher is frequently faced with the problem of trying to describe the relation between a response variable and a set of one or more input variables. Given data on input (predictor, independent) variables labeled x1, x2,..., xp and the associated response (output, dependent) variable y, the objective is to determine an equation relating output to input. The reasons for developing such an equation include the following:
  1. 1.

    to predict the response from a given set of inputs;

  2. 2.

    to determine the effect of an input on the response; and

  3. 3.

    to confirm, refute, or suggest theoretical or empirical relations.

To illustrate, the simplest situation is that of a single input for which a linear relation is assumed. Thus, if the relation is exact, it is given for appropriate values of β0 and β1 by
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References

  1. [1]
    Belsley, D.A., Kuh, E., and Welsch, R.E. (1980). Regression Diagnostics, Wiley, New York.Google Scholar
  2. [2]
    Daniel, C. and Woods, F.S. (1971). Fitting Equations to Data, Wiley, New York.Google Scholar
  3. [3]
    Draper, N.R. and Smith, H. (1966). Applied Regression Analysis, Wiley, New York.Google Scholar
  4. [4]
    Gunst, R.F. and Mason, R.L. (1980). Regression Analysis and Its Applications, Marcel Dekker, New York.Google Scholar
  5. [5]
    Neter, J. and Wasserman, W. (1974). Applied Linear Statistical Models, Richard D. Irwin. Homewood, Illinois.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Irwin Greenberg
    • 1
  1. 1.George Mason UniversityFairfaxUSA