# Ch 24: Variance, Probability & Distributions

### About This Chapter

## Variance, Probability & Distributions - Chapter Summary

In this chapter, you'll find short video lessons that simplify variance probability and distribution topics. Our expert instructors define topics like binomial and normal distribution, random variables, sample variance and much more. When you're finished with the chapter, you'll be able to:

- Evaluate examples of population and sample variance
- Graph probability distributions that are associated with random variables
- Interpret a continuous random variable's expected value
- Find expected values and theoretically develop continuous probability distributions
- Approximate binomial probabilities through normal distribution
- Define binomial distribution

The chapter comes with multiple-choice quizzes to help you check your understanding of important lesson topics. Be sure to take the chapter's multiple-choice exam, and if you need any help understanding the material, our instructors will be happy to assist you. You can also access these resources on any device that has an Internet connection.

### 1. Population & Sample Variance: Definition, Formula & Examples

Population and sample variance can help you describe and analyze data beyond the mean of the data set. In this lesson, learn the differences between population and sample variance.

### 2. Graphing Probability Distributions Associated with Random Variables

What's a random variable? Does it have anything to do with gambling? What's the difference between a continuous and a discrete variable? This lesson explains the difference and how to graph each one.

### 3. Finding & Interpreting the Expected Value of a Continuous Random Variable

How can you find the expected value of something like height distributions? This lesson explains how to find and interpret the expected value of a continuous random variable.

### 4. Developing Continuous Probability Distributions Theoretically & Finding Expected Values

What is an expected value? How can you tell how many time you should expect a coin to land on heads out of several flips? This lesson will show you the answers to both questions!

### 5. Using Normal Distribution to Approximate Binomial Probabilities

Binomial probabilities describe processes in our world. Learn how to create and interpret a binomial probability distribution graph, and discover how the normal distribution can form a good approximation of the binomial distribution.

### 6. Binomial Distribution: Definition, Formula & Examples

You have a probability distribution to create, which one do you use? That depends. In this lesson, learn about binomial distributions, get examples and criteria for their use, and learn how to calculate the binomial distribution formula.

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### Other Chapters

Other chapters within the MHT-CET: Practice & Study Guide course

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