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 x 1, x 2,..., x p 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.
to predict the response from a given set of inputs;
- 2.
to determine the effect of an input on the response; and
- 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
The determination of β0 and β1 in this case is easy, requiring only two distinct pairs of observations (x 1, y 1) and (x 2, y 2).
In general, the...
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References
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Neter, J. and Wasserman, W. (1974). Applied Linear Statistical Models, Richard D. Irwin. Homewood, Illinois.
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© 2001 Kluwer Academic Publishers
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Greenberg, I. (2001). Regression analysis . In: Gass, S.I., Harris, C.M. (eds) Encyclopedia of Operations Research and Management Science. Springer, New York, NY. https://doi.org/10.1007/1-4020-0611-X_871
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DOI: https://doi.org/10.1007/1-4020-0611-X_871
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