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Section 6.1 Introduction

When motivating our definition of probability you may have noticed that we modeled our definition on the relative frequency of equally-likely outcomes. In this chapter you will develop the theoretical formulas which can be used to model equally-likely outcomes.

In this chapter, you will investigate the following distributions:

  1. Discrete Uniform - each of a finite collection of outcomes is equally likely and prescribed a "position" and X measures the position of an item selected randomly from the outcomes.
  2. Continuous Uniform - an interval of values is possible with sub-intervals of equal length having equal probabilities and X measures a location inside that interval.
  3. Hypergeometric - each of a finite collection of values are equally likely and grouped into two classes (successes vs failures) and a subset of that collection is extracted with X measuring the number of successes in the sample.