About This Chapter
Who's it for?
Anyone who needs help learning or mastering college statistics material will benefit from taking this course. There is no faster or easier way to learn college statistics. Among those who would benefit are:
- Students who have fallen behind in understanding random variables or working with the expected value of a discrete random variable
- Students who struggle with learning disabilities or learning differences, including autism and ADHD
- Students who prefer multiple ways of learning math (visual or auditory)
- Students who have missed class time and need to catch up
- Students who need an efficient way to learn about discrete probability distributions
- Students who struggle to understand their teachers
- Students who attend schools without extra math learning resources
How it works:
- Find videos in our course that cover what you need to learn or review.
- Press play and watch the video lesson.
- Refer to the video transcripts to reinforce your learning.
- Test your understanding of each lesson with short quizzes.
- Verify you're ready by completing the Discrete Probability Distributions chapter exam.
Why it works:
- Study Efficiently: Skip what you know; review what you don't.
- Retain What You Learn: Engaging animations and real-life examples make topics easy to grasp.
- Be Ready on Test Day: Use the Discrete Probability Distributions chapter exam to be prepared.
- Get Extra Support: Ask our subject-matter experts any discrete probability distributions question. They're here to help!
- Study With Flexibility: Watch videos on any web-ready device.
Students will review:
This chapter helps students review the concepts in a Discrete Probability Distributions unit of a standard college statistics course. Topics covered include:
- Developing discrete probability distributions theoretically and finding expected values
- Comparing game strategies using expected values
- How to apply discrete probability concepts to problem solving
- Finding binomial probabilities using formulas or tables
- Mean and standard deviation of a binomial random variable
1. 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.
2. Finding & Interpreting the Expected Value of a Discrete Random Variable
Discrete random variables appear in your life a lot more than you think. You can use expected values to find the probability of a discrete random variable, as shown in this lesson.
3. 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.
4. 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.
5. 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.
6. Blackjack: Finding Expected Values of Games of Chance with Cards
In this video we learn about games of cards, and how to calculate probabilities. We look at the game of Blackjack and calculate the probability of getting certain hands. In addition we demonstrate how to calculate the expected value of a game that involves betting.
7. Lotteries: Finding Expected Values of Games of Chance
Most of us won't have a problem with winning the lottery. But is it a realistic goal? Do you really have a chance? In this lesson, learn how luck and probability collide when finding expected values in games of chance.
8. Comparing Game Strategies Using Expected Values: Process & Examples
While statistics and probability leave a lot to chance, we can use expected values to help inform our decisions. This lesson shows us how to use expected values to make the best determinations possible.
9. How to Apply Discrete Probability Concepts to Problem Solving
Discrete probability concepts, such as expected value, success, and failure, can be used to help you solve real-world problems and inform you when making decisions.
10. Binomial Experiments: Definition, Characteristics & Examples
Binomial experiments happen in your everyday life far more often than you might think. In this lesson, you will learn the characteristics of binomial experiments that will help you identify them.
11. Finding Binomial Probabilities Using Formulas: Process & Examples
You can find the probability of getting a certain number of successes when conducting a binomial experiment. In this lesson, you will learn how to find this information using the binomial probabilities formula.
12. Practice Problems for Finding Binomial Probabilities Using Formulas
In this lesson, you will review the binomial probability formula and the combination formula. Then follow along with the practice problems and see if you've mastered these concepts!
13. Finding Binomial Probabilities Using Tables
A binomial probability table can look intimidating to use. However, it can make your life a lot easier when trying to figure out binomial probabilities. This lesson will teach you how to read those tables.
14. Mean & Standard Deviation of a Binomial Random Variable: Formula & Example
When working with binomial random variables and experiments, it is important to understand the mean and standard deviation. In this lesson, you will learn how to analyze binomial experiments using the mean and standard deviation of a binomial random variable.
15. Solving Problems with Binomial Experiments: Steps & Example
Sometimes when conducting research you will need to use binomial experiments to solve problems. In this lesson, you will learn about binomial experiments and how to use probability to solve problems.
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Other chapters within the Introduction to Statistics: Help and Review course