# Working with Probability

• Glenn Ledder
Chapter
Part of the Springer Undergraduate Texts in Mathematics and Technology book series (SUMAT)

## Abstract

Chapter 3 was a coherent presentation of material on descriptive statistics and probability distributions, which are viewed as theoretical populations. Chapter 4 follows with seven sections that are grouped into three themes. The first four sections treat inferential statistics, beginning with an introductory section that introduces the central question of whether a test population is the same as or different from a general population. This is followed by a section that presents the Cramer–von Mises test for consistency of a data set with a normal distribution. This test serves as a convenient analytical tool for observing the convergence as n of distributions of means of samples of size n to a normal distribution, regardless of the underlying distribution from which the samples are drawn. Section 4.3 presents the central limit theorem, which is then used in Section 4.4 to address statistical inference. Section 4.5 serves as a brief introduction to maximum likelihood, and the chapter closes with two sections on conditional probability. Many of the problems use real data sets that were introduced in Chapterer 3.

## Keywords

Conditional Probability Likelihood Function Success Probability Sequence Rule Bernoulli Trial
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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