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Hypothesis Testing Theory

In: Mathematical Statistics for Economics and Business

Author

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  • Ron C. Mittelhammer

    (Washington State University, School of Economic Sciences)

Abstract

A primary goal of scientific research often concerns the verification or refutation of assertions, conjectures, currently accepted laws, or descriptions relating to a given economic, sociological, psychological, physical, or biological process or population. Statistical hypothesis testing concerns the use of probability samples of observations from processes or populations of interest, together with probability and mathematical statistics principles, to judge the validity of stated assertions, conjectures, laws, or descriptions in such a way that the probability of falsely rejecting a correct hypothesis can be controlled, while the probability of rejecting false hypotheses is made as large as possible. The precise nature of the types of errors that can be made, how the probabilities of such errors can be controlled, and how one designs a test so that the probability of rejecting false hypotheses is as large as possible is the subject of this chapter.

Suggested Citation

  • Ron C. Mittelhammer, 2013. "Hypothesis Testing Theory," Springer Books, in: Mathematical Statistics for Economics and Business, edition 2, chapter 9, pages 523-607, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-5022-1_9
    DOI: 10.1007/978-1-4614-5022-1_9
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