Hypothesis testing and confidence intervals concerning one or two means

Pierre Jolicoeur
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Pierre Jolicoeur: University of Montreal, Department of Biological Science

Chapter Chapter 9 in Introduction to Biometry, 1999, pp 42-62 from Springer

Abstract: Abstract In this chapter, the continuous variate X under study will be assumed to follow a normal probability distribution (chapter 5) of which the mean is μx and the variance σ x 2 : X ← N (µx,σ x 2 ). However, the methods discussed here will retain their validity in many other cases where the variate X is not normally distributed but can be transformed into another variate Y=g(X) having a normal distribution N (µy,σ x 2 ). In such cases, once the statistical analysis of the transformed variate Y has been completed through methods based on normal theory, results can be reexpressed with respect to the original (untransformed) variate X by using the inverse transformation X=g-1(Y). For instance, if the original variate X follows a lognormal distribution (chapter 14), the transformed variate Y=loge(X) has a normal distribution and the results of the statistical analysis of Y can be reexpressed with respect to X thanks to the transformation X=exp(Y).

Keywords: Alternative Hypothesis; Prediction Interval; Bilateral Symmetry; Individual Observation; Acceptance Region (search for similar items in EconPapers)
Date: 1999
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DOI: 10.1007/978-1-4615-4777-8_10

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