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Regression as an Analytical Tool

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  • P. G. Moore

Abstract

In this article Dr Moore first illustrates some pitfalls in the application of simple regression methods to industrial problems, and goes on to discuss the usefulness of multiple regression as an analytical tool. However, when there are potentially many independent variables, the amount of computation for a complete analysis is very large; two short‐cut methods are described here in which much less computation is required.

Suggested Citation

  • P. G. Moore, 1962. "Regression as an Analytical Tool," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 11(2), pages 106-119, June.
    • Handle: RePEc:bla:jorssc:v:11:y:1962:i:2:p:106-119
    DOI: 10.2307/2985537
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    Cited by:

    1. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis, 2016. "Statistical Modeling Of Stock Returns: Explanatory Or Descriptive? A Historical Survey With Some Methodological Reflections," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 149-164, February.
    2. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis, "undated". "Statistical Modeling of Stock Returns: Explanatory or Descriptive? A Historical Survey with Some Methodological Reflections," DEOS Working Papers 1331, Athens University of Economics and Business.
    3. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis, 2012. "Statistical Modeling of Stock Returns: A Historical Survey with Methodological Reflections," DEOS Working Papers 1226, Athens University of Economics and Business.

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