Ch 53: TExMaT Master Mathematics Teacher 8-12: Continuous Probability Distributions

About This Chapter

Use this chapter's video lessons to review continuous probability concepts covered on the TExMaT Master Mathematics Teacher 8-12 exam. Take the multiple-choice quizzes that follow to get practice working with these probability distributions.

TExMaT Master Mathematics Teacher 8-12: Continuous Probability Distributions - Chapter Summary

Get a refresher on the uses of continuous probability distributions when you watch this chapter's video lessons. Instructors discuss the following concepts associated with probability distributions and their graphs to prepare you for questions on the TExMaT Master Mathematics Teacher 8-12 exam:

  • Graphing random value probability distributions
  • Expected values of continuous random variables
  • Normal distribution
  • The empirical rule
  • Approximating binomial probabilities

Watch the videos to review step-by-step instructions for graphing probability distributions, finding expected values, and estimating binomial probabilities. You can also scan the transcripts to quickly identify key vocabulary terms. Both formats allow you to work at your own pace, and the multiple-choice quizzes could prove useful for measuring your understanding of these topics.

TExMaT Master Mathematics Teacher 8-12: Continuous Probability Distributions - Chapter Objectives

Master Mathematics Teacher certification is available to experienced high school math teachers interested in mentoring their fellow Texas educators. Requirements include passing scores on the TExMaT Master Mathematics Teacher 8-12 exam. Examinees must answer 90 multiple-choice questions and complete a case study assignment designed to gauge their subject area knowledge and teaching expertise.

Use the lessons in this chapter to prepare for exam content testing your ability to work with continuous random variables and probability distributions as well as your familiarity with such concepts as expected value, standard deviation, normal distribution, and binomial probabilities. These types of questions fall under the probability and statistics content domain, which makes up around 14% of exam content.

6 Lessons in Chapter 53: TExMaT Master Mathematics Teacher 8-12: Continuous Probability Distributions
Test your knowledge with a 30-question chapter practice test
Graphing Probability Distributions Associated with Random Variables

1. 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.

Finding & Interpreting the Expected Value of a Continuous Random Variable

2. 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.

Developing Continuous Probability Distributions Theoretically & Finding Expected Values

3. 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!

Normal Distribution: Definition, Properties, Characteristics & Example

4. Normal Distribution: Definition, Properties, Characteristics & Example

In this lesson, we will look at the Normal Distribution, more commonly known as the Bell Curve. We'll look at some of its fascinating properties and learn why it is one of the most important distributions in the study of data.

Estimating Population Percentages from Normal Distributions: The Empirical Rule & Examples

5. Estimating Population Percentages from Normal Distributions: The Empirical Rule & Examples

If you've been working with z-scores for long, you probably get tired of checking those tables every time you need to check the area under the curve. Luckily, the empirical rule helps us memorize the most important values.

Using Normal Distribution to Approximate Binomial Probabilities

6. 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.

Chapter Practice Exam
Test your knowledge of this chapter with a 30 question practice chapter exam.
Not Taken
Practice Final Exam
Test your knowledge of the entire course with a 50 question practice final exam.
Not Taken

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