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Hypothesis testing and confidence intervals concerning one or two means

In: Introduction to Biometry

Author

Listed:
  • Pierre Jolicoeur

    (University of Montreal, Department of Biological Science)

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).

Suggested Citation

  • Pierre Jolicoeur, 1999. "Hypothesis testing and confidence intervals concerning one or two means," Springer Books, in: Introduction to Biometry, chapter 0, pages 42-62, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4615-4777-8_10
    DOI: 10.1007/978-1-4615-4777-8_10
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