Multiple Regression with Unbalanced Data

Article

Hinchen, John D.   (1970, ASQC)   Monsanto Company, St. Louis, MO

Journal of Quality Technology    Vol. 2    No. 1
QICID: 5042    January 1970    pp. 22-29
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Article Abstract

Regression analysis has become a very popular method for analyzing existing plant and research data. The existence of correlations among the independent variables is recognized as a major pitfall in the proper interpretation of such data. This paper outlines the errors in interpretation that may result when specific degrees of correlation exist. The situation is examined for a two-variable case, Fitting first and second degree models to data from sources of varying complexity. A computer was used to generate and analyze the data.

Keywords

Multiple regression,Statistical methods


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