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Ballinger, Clint Why inferential statistics are inappropriate for development studies and how the same data can be better used. unpublished. (Unpublished)

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    Abstract

    The purpose of this paper is twofold: 1) to highlight the widely ignored but fundamental problem of ‘superpopulations’ for the use of inferential statistics in development studies. We do not to dwell on this problem however as it has been sufficiently discussed in older papers by statisticians that social scientists have nevertheless long chosen to ignore; the interested reader can turn to those for greater detail. 2) to show that descriptive statistics both avoid the problem of superpopulations and can be a powerful tool when used correctly. A few examples are provided. The paper ends with considerations of some reasons we think are behind the adherence to methods that are known to be inapplicable to many of the types of questions asked in development studies yet still widely practiced.

    Item Type: Other
    Subjects: Mathematical and Computer Sciences > Statistics > Applied Statistics
    Mathematical and Computer Sciences > Statistics > Probability
    Mathematical and Computer Sciences > Statistics > Statistical Modelling
    Social studies > Economics
    Social studies > Human and Social Geography > Human and Social Geography not elsewhere classified
    Historical and Philosophical studies > Philosophy > Philosophy of Science
    Divisions: UNSPECIFIED
    Depositing User: Dr. Clint Ballinger
    Date Deposited: 20 Mar 2011 22:14
    Last Modified: 20 Mar 2011 22:14
    URI: http://opendepot.org/id/eprint/403

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