Abstract
To know how inferential tests work, it is important to understand the underpinnings associated with these tests. This chapter covers probability which is critical for all inferential tests and the likelihood of making a correct decision about a population based on a small sample taken from that population. This chapter considers characteristics associated with symmetrical and asymmetrical distributions. If it can be assumed that the population is symmetrically distributed, it is required that each level of the independent variable has similar dispersions. If the population is not normally distributed, nonparametric or distribution-free statistics should be considered. The center for the population can be estimated with a confidence interval, and tolerance limits can approximate a range of values representing the outcomes for the vast majority of the population.
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De Muth, J.E. (2019). Statistical Inference and Making Estimates of the Truth. In: Practical Statistics for Pharmaceutical Analysis. AAPS Advances in the Pharmaceutical Sciences Series, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-030-33989-0_3
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DOI: https://doi.org/10.1007/978-3-030-33989-0_3
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