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A hypothesis test involves the specification of one, or a number of competing, mathematically precise statements (statistical hypotheses), which can be tested using measured data. Hypothesis testing is one of the core elements of statistical inference, and one of the key activities in science. The activity of hypothesis testing is not standalone. Statistical hypotheses derive from research questions. Study designs develop from these questions and provide the data by which the statistical hypotheses can be tested. Thus, hypothesis testing is one step in an integrated process of scientific investigation. However, it is a critical step, and as such, there is much debate about the most appropriate way to go about it.
Overview
Hypothesis testing is one of the major strands of statistical inference, alongside parameter estimation and prediction (Diggle and Chetwynd 2014). A primary function of hypothesis testing is to provide a system by which to...
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References
Diggle, P. J., & Chetwynd, A. G. (2014). Statistics and scientific method: An introduction for students and researchers. Oxford: Oxford University Press.
Gigerenzer, G., Krauss, S., & Vitouch, O. (2004). The Null Ritual; What you always wanted to know about significance testing but were afraid to ask. In D. Kaplan (Ed.) The Sage handbook of quantitative methodology for the social sciences (pp. 391–408). Thousand Oaks, CA: Sage.
Gill, J. (2009). Bayesian methods: A social and behavioural sciences approach (2nd ed.). Boca Ranton: Chapman & Hall.
Jaynes, E. T. (2003). Probability theory: The logic of science. Cambridge: Cambridge University Press.
Jeffreys, H. (1961). Theory of probability (3rd ed.). Oxford: Oxford University Press/Clarendon Press.
Kass, R. E., & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90, 773–795.
Lehmann, E. L. (1993). The Fisher, Neyman-Pearson Theories of Testing Hypotheses: One Theory of Two? Journal of the American Statistical Association, 88, 1242–1249.
Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16, 225–237.
Szucs, D., & Ioannidis, J. P. A. (2016). When null hypothesis significance testing is unsuitable for research: A reassessment. doi: 10.1101/095570
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Booth, T., Doumas, A., Murray, A.L. (2017). Hypothesis Testing. In: Zeigler-Hill, V., Shackelford, T. (eds) Encyclopedia of Personality and Individual Differences. Springer, Cham. https://doi.org/10.1007/978-3-319-28099-8_1310-1
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DOI: https://doi.org/10.1007/978-3-319-28099-8_1310-1
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