Here are problems that are similar to the ones you might see on the exam. Be sure to also review old homework and workshop questions too. The exam will have both multiple choice and short answer questions.

Conditional Probability

These are tricky. Be sure you understand how these work in two-way tables and when you are given the probabilties. Also, make sure you understand the difference between the probability of A and B both happening, versus the probability of A given B.

Weighted Averages and Expected Value

Expected value is the weighted average of the outcomes in a probability model. Make sure you understand why it is called "expected" and how to calculate it. You should know the Law of Large Numbers too.

Random Variables

When we use a letter to represent the numerical outcome of a probability model, that letter is called a random variable. You should be comfortable with the way random variables are used in notation, and know how to find the expected value, variance, and standard deviation of a simple random variable.

Continuous vs. Discrete Random Variables

You should be able to tell the difference between random variables that are continuous (like height and weight) and ones that are discrete (like number of siblings or the result of rolling some dice).

Normal Distribution

The test will have several questions about normal distributions. Make sure you can do all of the calculations, and know the 68-95-99.7 rule.

Sampling Distributions

Make sure you know the shape, center, and spread for the sampling distributions of the sample mean \(\bar{x}\) and the sample proportion \(\hat{p}\). Be sure you can describe how they change as the sample size gets larger.