This course has several prerequisites. The most salient one is MATH 321. In that course, you learned a lot: probability distributions, moments, moment-generating functions, and the Central Limit Theorem. This preliminary module for MATH 322 seeks to refresh your memory on what you have already learned so that you can use it in this course.

Objectives

By the end of this module, the student will

• be familiar with the following probability distributions:
• Binomial
• Chi-Square
• Exponential
• F
• Gamma
• Geometric
• Negative Binomial
• Normal (Gaussian)
• Poisson
• Student’s t
• calculate moments for probability distributions
• calculate the moment-generating function for distributions
• sketch the graph of each distribution
• calculate the probability function for a function of random variables
• determine the distribution of sums, minimums, and maximums of random variables
• know the properties of probability distributions
• do the above above without the help of Mathematica

Readings

• No Specific Reading

I strongly recommend you use your MATH 322 book for review as much as possible. This will help you learn what information it contains and where that information is located.

Example Scripts

The following R scripts provide some additional practice in statistical computing. Consider these to be required activities.

• Monte Carlo Simulation
• Test Evaluation
• Bootstrapping

Statistical Computing Activity

• SCA 0: Distributions in R

Assignment

• Assignment 0