Ch 38: Distribution & Inference in Statistics

About This Chapter

Use the following video lessons and quizzes to help you understand the central limit theorem and the law of large numbers. Learn how to solve problems using normal distributions and z-scores.

Distribution & Inference in Statistics - Chapter Summary

Instructors begin this chapter on normal distribution by examining its properties. You can take a look at this bell curve's symmetrical center and single mode, as well as the asymptotes at either end, and learn how the normal distribution is used to estimate population percentages.

The relationship between normal distributions, standard deviations and z-scores is covered as well. Video lessons show you the processes involved in finding these measures and illustrate the uses of z-scores to estimate areas.

The chapter concludes with lessons relating normal distribution to two main probability theorems, the central limit theorem and the law of large numbers, both of which can be used to describe the sampling distributions and expected values of an experiment's outcomes. By the time you finish these lessons, you should be familiar with the following:

  • Characteristics of normal distribution
  • The steps for finding and using z-scores
  • Applications of the law of large numbers
  • Uses of the central limit theorem

This chapter contains plenty of resources to help you master the concept of normal distribution. In addition to illustrated videos taught by experienced instructors, there are transcripts with embedded links to text lessons that outline key statistics terminology. Lessons also include practice problems, as well as self-assessment quizzes, to help ensure you've got a firm grasp of the main ideas.

5 Lessons in Chapter 38: Distribution & Inference in Statistics
Test your knowledge with a 30-question chapter practice test
Normal Distribution: Definition, Properties, Characteristics & Example

1. 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

2. 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.

Binomial Distribution: Definition, Formula & Examples

3. Binomial Distribution: Definition, Formula & Examples

You have a probability distribution to create, which one do you use? That depends. In this lesson, learn about binomial distributions, get examples and criteria for their use, and learn how to calculate the binomial distribution formula.

Understanding the Law of Large Numbers

4. Understanding the Law of Large Numbers

The law of large numbers is a concept that is often misunderstood in statistics. In this lesson, you will learn the real meaning of the law of large numbers and how it is employed.

Sampling Distributions & the Central Limit Theorem: Definition, Formula & Examples

5. Sampling Distributions & the Central Limit Theorem: Definition, Formula & Examples

Want proof that all of this normal distribution talk actually makes sense? Then you've come to the right place. In this lesson, we look at sampling distributions and the idea of the central limit theorem, a basic component of statistics.

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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