About This Chapter
How It Works:
- Identify the lessons in the McDougal Littell Probability & Data Analysis chapter with which you need help.
- Find the corresponding video lessons with this companion course chapter.
- Watch fun videos that cover the probability and data analysis 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:
- Probabilities for compound, simple and complementary events
- Tools to calculate permutations
- The easiest way to solve math combinations
- Either/or probability
- How to apply the addition rule of probability
- Examples of independent and dependent events
- The multiplication rule of probability
- Conditions of random sampling
- Methods of systematic random sampling
- How to measure mean, median and mode
- Ways to write stem & leaf displays
- Steps to interpret box plots
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1. 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.
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. How to Calculate the Probability of Permutations
In this lesson, you will learn how to calculate the probability of a permutation by analyzing a real-world example in which the order of the events does matter. We'll also review what a factorial is. We will then go over some examples for practice.
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.
5. Either/Or Probability: Overlapping and Non-Overlapping Events
Statistics is the study and interpretation of a set of data. One area of statistics is the study of probability. This lesson will describe how to determine the either/or probability of overlapping and non-overlapping events.
6. The Addition Rule of Probability: Definition & Examples
In this lesson, you will learn the differences between mutually exclusive and non-mutually exclusive events and how to find the probabilities of each using the Addition Rule of Probability.
7. 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.
8. The Multiplication Rule of Probability: Definition & Examples
The Multiplication Rule of Probability is a concept you will use frequently when solving probability equations. In this lesson, learn the two different scenarios in which you will use the multiplication rule of probability.
9. What is Random Sampling? - Definition, Conditions & Measures
Random sampling is used in many research scenarios. In this lesson, you will learn how to use random sampling and find out the benefits and risks of using random samples.
10. Systematic Random Samples: Definition, Formula & Advantages
Systematic random sampling is a great way to randomly collect data on a population without the hassle of putting names in a bag or using a random number generator. In this lesson, learn all about how and when to use systematic random sampling.
11. Mean, Median & Mode: Measures of Central Tendency
By describing the data using central tendency, a researcher and reader can understand what the typical score looks like. In this lesson, we will explore in more detail these measures of central tendency and how they relate to samples and populations.
12. Creating & Reading Stem & Leaf Displays
Every once in a while you will come across stem-and-leaf displays in statistics. These displays can be very useful in identifying all of the values in a data set while still visually representing the data.
13. Creating & Interpreting Histograms: Process & Examples
Creating histograms can help you easily identify and interpret data. This lesson will give you several examples to better understand histograms and how to create them.
14. Creating & Interpreting Box Plots: Process & Examples
Box plots are an essential tool in statistical analysis. This lesson will help you create a box plot and understand its meaning. When you are finished, test your understanding with a short quiz!
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Other chapters within the McDougal Littell Algebra 1: Online Textbook Help course
- McDougal Littell Algebra 1 Chapter 1: Expressions, Equations & Functions
- McDougal Littell Algebra 1 Chapter 2: Properties of Real Numbers
- McDougal Littell Algebra 1 Chapter 3: Solving Linear Equations
- McDougal Littell Algebra 1 Chapter 4: Graphing Linear Equations & Functions
- McDougal Littell Algebra 1 Chapter 5: Writing Linear Equations
- McDougal Littell Algebra 1 Chapter 6: Solving & Graphing Linear Inequalities
- McDougal Littell Algebra 1 Chapter 7: Systems of Linear Equations & Inequalities
- McDougal Littell Algebra 1 Chapter 8: Exponents & Exponential Functions
- McDougal Littell Algebra 1 Chapter 9: Polynomials & Factoring
- McDougal Littell Algebra 1 Chapter 10: Quadratic Equations & Functions
- McDougal Littell Algebra 1 Chapter 11: Radicals & Geometry Connections
- McDougal Littell Algebra 1 Chapter 12: Rational Equations & Functions