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One Data, Many Tests


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1 Indian Institute of Management Ahmedabad, Gujarat, India
     

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In many areas of research in management, social science, medical science, genomics, business studies and psychology it is a common practice for researchers to test their theoretical understanding of a phenomenon through formulation of appropriate hypotheses which can be proved or disproved on the basis of data. These researchers argue that if the data provides support to the formulated hypotheses then it can be concluded that the theory based on which these hypotheses were derived is also empirically validated. Typically a piece of research may depend on testing more than one hypothesis and the empirical validation of the theory requires all these hypotheses being supported.
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  • Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289-300.

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  • One Data, Many Tests

Abstract Views: 359  |  PDF Views: 0

Authors

Arnab Kumar Laha
Indian Institute of Management Ahmedabad, Gujarat, India

Abstract


In many areas of research in management, social science, medical science, genomics, business studies and psychology it is a common practice for researchers to test their theoretical understanding of a phenomenon through formulation of appropriate hypotheses which can be proved or disproved on the basis of data. These researchers argue that if the data provides support to the formulated hypotheses then it can be concluded that the theory based on which these hypotheses were derived is also empirically validated. Typically a piece of research may depend on testing more than one hypothesis and the empirical validation of the theory requires all these hypotheses being supported.

References