Abstract
Hypothesis testing is one of the main objectives of conducting scientific studies and performing statistical analysis. In this chapter, we assume that the hypothesis of interest is clearly defined, and the data have been collected for the purpose of evaluating the hypothesis. Using the empirical evidence provided by the data, we need to decide whether we should reject or accept the hypothesis. Here, we mainly focus on hypotheses specified in terms of the population mean or the population proportion with respect to a specific characteristic of the population. For such cases, we discuss some simple methods for quantifying the evidence provided by the data in support of the hypothesis. We then talk about some commonly used approaches for deciding whether the hypothesis should be rejected or accepted based on the evidence provided by the observed data.
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© 2012 Springer Science+Business Media, LLC
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Shahbaba, B. (2012). Hypothesis Testing. In: Biostatistics with R. Use R!. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1302-8_7
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DOI: https://doi.org/10.1007/978-1-4614-1302-8_7
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-1301-1
Online ISBN: 978-1-4614-1302-8
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