Ch 31: TExES Math 4-8: Mathematical Probability

About This Chapter

Refresh your memory on mathematical probability with this chapter's engaging video lessons. You should be able to correctly answer any probability questions on the TExES Math 4-8 exam after you're done with this chapter.

TExES Math 4-8: Mathematical Probability - Chapter Summary

You'll get to effectively strengthen your understanding of probability with this chapter as you prepare for the TExES Math 4-8 test. You'll find the following topics covered in this chapter:

  • Probability of compound, simple and complementary events
  • Probability of dependent and independent events
  • Math combinations and sets
  • Calculating permutations
  • Types of random variables
  • Normal distribution characteristics
  • Classical approaches to probability
  • How to develop discrete probability distributions

You can complete a short practice quiz after each of the lessons in this chapter. If you have any questions, you can easily contact instructors through the Teacher tab.

10 Lessons in Chapter 31: TExES Math 4-8: Mathematical Probability
Test your knowledge with a 30-question chapter practice test
Mathematical Sets: Elements, Intersections & Unions

1. Mathematical Sets: Elements, Intersections & Unions

Today we're going to explore mathematical sets, which are surprisingly simple! Sets are just collections of any objects or concepts, also known as elements, that can be related to each other through union or intersection.

Probability of Simple, Compound and Complementary Events

2. Probability of Simple, Compound and Complementary Events

Simple, compound, and complementary events are different types of probabilities. Each of these probabilities are calculated in a slightly different fashion. In this lesson, we will look at some real world examples of these different forms of probability.

Probability of Independent and Dependent Events

3. Probability of Independent and Dependent Events

Sometimes probabilities need to be calculated when more than one event occurs. These types of compound events are called independent and dependent events. Through this lesson, we will look at some real-world examples of how to calculate these probabilities.

Math Combinations: Formula and Example Problems

4. Math Combinations: Formula and Example Problems

Combinations are an arrangement of objects where order does not matter. In this lesson, the coach of the Wildcats basketball team uses combinations to help his team prepare for the upcoming season.

How to Calculate a Permutation

5. How to Calculate a Permutation

A permutation is a method used to calculate the total outcomes of a situation where order is important. In this lesson, John will use permutations to help him organize the cards in his poker hand and order a pizza.

Relative Frequency & Classical Approaches to Probability

6. Relative Frequency & Classical Approaches to Probability

To understand probability, it is important to understand the foundations. In this lesson, you will learn about relative frequency and the foundations of understanding probability.

Random Variables: Definition, Types & Examples

7. Random Variables: Definition, Types & Examples

This lesson defines the term random variables in the context of probability. You'll learn about certain properties of random variables and the different types of random variables.

Developing Discrete Probability Distributions Theoretically & Finding Expected Values

8. Developing Discrete Probability Distributions Theoretically & Finding Expected Values

In this lesson, we will look at generating a theoretical probability distribution for a discrete random variable and introduce the concept of expected value.

Developing Discrete Probability Distributions Empirically & Finding Expected Values

9. Developing Discrete Probability Distributions Empirically & Finding Expected Values

In this lesson, we will look at creating a discrete probability distribution given a set of discrete data. We will also look at determining the expected value of the distribution.

Normal Distribution: Definition, Properties, Characteristics & Example

10. 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.

Chapter Practice Exam
Test your knowledge of this chapter with a 30 question practice chapter exam.
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Practice Final Exam
Test your knowledge of the entire course with a 50 question practice final exam.
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Other Chapters

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