Download Review Topics for Exam 2

Statistics 2014, Fall 2015
Exam 2 Review Topics
Chapter 5 – Probability
Random experiment.
Sample space
Events: Simple event; Compound event.
Assigning probabilities to events:
Classical approach: equally likely outcomes
Relative frequency (empirical) approach
Interpreting a probability, using the relative frequency (empirical) approach
Mutually exclusive events
Complement of an event – Complement Rule
Union of events
Intersection of events
Basic Laws of Probability: (Kolmogorov’s Axioms):
1) For any event A, 0  P(A)  1.
2) P(S) = 1. In other words, the outcome of the random experiment is certain to be in the
sample space.
3) If two events A and B are mutually exclusive, then P( A OR B)  P( A)  P( B) .
Equally likely outcomes due to random selection
Addition Rule for Non-Mutually Exclusive Events
Conditional Probability
Independent events
Multiplication Rule for independent events
Chapter 6 – Discrete Probability Distributions
Random variables, discrete and continuous
Probability distribution
Required Properties of a Discrete Probability Distribution
Expectation, or mean, of a probability distribution of a discrete random variable X.
How to interpret the mean, using the relative frequency (empirical) approach.
Variance of a discrete random variable X
Conditions for a binomial experiment
Binomial probability distribution; binomial random variable X
Finding binomial probabilities using the TI-83
Mean, variance and standard deviation for the Binomial Distribution.
Chapter 7 – The Normal Probability Distribution
Characteristics of normal distributions
The Empirical Rule:
Standard Normal Distribution
Finding normal probabilities using the TI-83 calculator
Inverting the process: finding percentiles of a normal distribution.