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1. Experiment, Outcomes, and Sample space
2. Random Variables
3. Probability Distribution of a Discrete Random
Variable
4. The Binomial Probability Distribution
5. The Hypergeometric Probability Distribution
6. The Poisson Probability Distribution
7. Continuous Random Variables
8. The Normal Distribution
9. The Normal Approximation to the Binomial
Distribution

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An experiment is a process that, when performed, results in one and only one of many observations. These observations are called the outcomes of the experiment.
The collection of all outcomes for an experiment is called a sample space.
Table 1 Examples of Experiments, Outcomes, and Sample
Spaces
Experiment

Outcomes

Sample Space

Toss a coin once

Head, Tail

S= { Head, Tail}

Roll a die once

1, 2, 3, 4, 5, 6

S= {1, 2, 3, 4, 5, 6}

Toss a coin twice

HH, HT, TH, TT

S= { HH, HT, TH, TT}

Play lottery

Win, Lose

S= {Win, Lose}

Take a test

Pass, Fail

S= {Pass, Fail}

Select a worker

Male, Female

S= { Male, Female}

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A random variable is a variable whose value is determined by the outcome of a random experiment. A random variable that assumes countable values is called a discrete random variable.
A random variable that can assume any value contained in one or more intervals is called a continuous random variable.
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Examples of discrete random variables
1. The number of heads obtained in three tosses of a coin
2. The number of complaints received at the office of an airline on a given day
3. The number of customers who visit a bank during any given hour
Examples of continuous random variables
1. The weight of a person
2. The time taken to commute from home to work 3. The price of a house
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The probability distribution of a discrete random