# Ch 12: McDougal Littell Algebra 2 Chapter 12: Probability and Statistics

### About This Chapter

## How it works:

- Identify the lessons in the McDougal Littell Algebra 2 Probability and Statistics chapter with which you need help.
- Find the corresponding video lessons within this companion course chapter.
- Watch fun videos that cover the probability and statistics topics you need to learn or review.
- Complete the quizzes to test your understanding.
- If you need additional help, rewatch the videos until you've mastered the material or submit a question for one of our instructors.

## Students will learn:

- The fundamental counting principle
- Permutations
- Math combinations
- The Binomial Theorem
- Probabilities of simple, compound and complementary events
- Probabilities of dependent and independent events
- The 'at least one' rule
- Simple conditional probabilities
- The relationship between conditional probabilities and independence
- Random variables
- Empirical and theoretical discrete probability distributions
- Expected values in games of chance
- Normal distribution

*McDougal Littell Algebra 2 is a registered trademark of Houghton Mifflin Harcourt, which is not affiliated with Study.com.*

### 1. How to Use the Fundamental Counting Principle

There are many situations in which you will have to make several decisions simultaneously. The fundamental counting principle will help you determine how many different possible outcomes there are when you have to make multiple simultaneous decisions.

### 2. 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.

### 3. 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.

### 4. How to Use the Binomial Theorem to Expand a Binomial

In this video lesson, you will see what the binomial theorem has in common with Pascal's triangle. Learn how you can use Pascal's triangle to help you to easily expand a binomial.

### 5. 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.

### 6. 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.

### 7. Probability of Independent Events: The 'At Least One' Rule

Occasionally when calculating independent events, it is only important that the event happens once. This is referred to as the 'At Least One' Rule. To calculate this type of problem, we will use the process of complementary events to find the probability of our event occurring at least once.

### 8. How to Calculate Simple Conditional Probabilities

Conditional probability, just like it sounds, is a probability that happens on the condition of a previous event occurring. To calculate conditional probabilities, we must first consider the effects of the previous event on the current event.

### 9. The Relationship Between Conditional Probabilities & Independence

Conditional and independent probabilities are a basic part of learning statistics. It's important that you can understand the similarities and differences between the two as discussed in this lesson.

### 10. Applying Conditional Probability & Independence to Real Life Situations

It can be really confusing learning how to apply conditional and independent probability to real-life situations. This lesson focuses on several examples and practice problems to help you learn how to find conditional probability.

### 11. 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.

### 12. 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.

### 13. 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.

### 14. Dice: Finding Expected Values of Games of Chance

This lesson examines the various combinations and probabilities behind rolling dice. We will look at a game of dice and what to expect to win or lose in a game. In addition we will extend these concepts to playing with different sided dice.

### 15. 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.

### 16. Using the Normal Distribution: Practice Problems

In this lesson, we will put the normal distribution to work by solving a few practice problems that help us to really master all that the distribution, as well as Z-Scores, have to offer. Review the concepts with a short quiz at the end.

### 17. 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.

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### Other Chapters

Other chapters within the McDougal Littell Algebra 2: Online Textbook Help course

- McDougal Littell Algebra 2 Chapter 1: Equations and Inequalities
- McDougal Littell Algebra 2 Chapter 2: Linear Equations and Functions
- McDougal Littell Algebra 2 Chapter 3: Systems of Linear Equations and Inequalities
- McDougal Littell Algebra 2 Chapter 4: Matrices and Determinants
- McDougal Littell Algebra 2 Chapter 5: Quadratic Functions
- McDougal Littell Algebra 2 Chapter 6: Polynomials and Polynomial Functions
- McDougal Littell Algebra 2 Chapter 7: Powers, Roots, and Radicals
- McDougal Littell Algebra 2 Chapter 8: Exponential and Logarithmic Functions
- McDougal Littell Algebra 2 Chapter 9: Rational Equations and Functions
- McDougal Littell Algebra 2 Chapter 10: Quadratic Relations and Conic Sections
- McDougal Littell Algebra 2 Chapter 11: Sequences and Series
- McDougal Littell Algebra 2 Chapter 13: Trigonometric Ratios and Functions
- McDougal Littell Algebra 2 Chapter 14: Trigonometric Graphs, Identities, and Equations