Exam 1 Study Guide

Chapter 1

Measures of Location

You should be familiar with the following definitions, and able to use a spreadsheet to compute them for a given set of data values:

• mean
• median
• trimmed mean
• percentile
• quartile

You should know which measures are sensitive to outliers.

You should be aware of the difference between sample values and population values for these measures.

Measures of Variability

You should be familiar with the following definitions, and able to use a spreadsheet to compute them for a given set of data values:

• range
• variance
• standard deviation
• interquartile range (the difference between the third quartile and the first quartile), roughly equivalent to what the author calls the fourth spread. (The interquartile range is easier to calculate with a spreadsheet)

You should know which measures are sensitive to outliers.

You should be aware of the difference between sample values and population values for these measures.

Chapter 2

Sample Spaces and Events

You should be familiar with the following definitions:

• event
• simple event
• compound event
• set union
• set compliment
• set intersection
• mutually exclusive or disjoint events

You should be able to use the properties of probability on pages 54 and 55.

Counting Tecniques

You should be familiar with the following definitions:

• permutation
• combination

You should be able to use a spreadsheet to compute permutations and combinations, understand the difference between them and know which one to use in a problem.

You should be able to apply the product rules for ordered pairs and k-tuples.

Conditional Probability

You should be able to apply the definition of conditional probability, the law of total probability, and Baye's Theorem.

Independence

You should be able to apply the definition of independence and the multiplication rule for two or more events.

Chapter 3

Random Variables

You should be familiar with the following definitions:

• random variable
• Bernoulli random variable
• Discrete random variable
• Continuous random variable

Probability Distributions

You should be familiar with the following definitions:

• probability distribution or probability mass function
• parameter of a distribution
• cumulative distribution function

You should be able to use the probability mass function or cumulative distribution function to find the probability of events.

Expected Values

You should be familiar with the following definitions and able to apply them:

• expected value or mean value of a random variable
• expected value of a function of a random variable
• variance of a random variable
• standard deviation of a random variable

You should be able to use the probability mass function to find expected values, possibly with a spreadsheet.

The Binomial Distribution

You should be familiar with the definition of a binomial experiment and a binomial random variable.

You should be able to use a spreadsheet to compute single-value and cumulative binomial probabilities.