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Ch 56: NES Math: Sampling

About This Chapter

Let us help you review information on sampling, including types of samples, formulas and the central limit theorem as you study for the NES Math test. This chapter of the study guide provides a variety of ways to aid in your test preparation.

NES Math: Sampling - Chapter Summary

Use this chapter's lessons on samples and analysis techniques as part of your review resources as you get ready for the NES Math test. Our short videos, quizzes and other study tools can help you brush up on topics such as:

  • Definition and measures of random sampling
  • Simple, stratified, cluster and systematic random samples
  • The central limit theorem on sampling distributions
  • How to find the mean and standard error of the sampling distribution
  • How to find probabilities about means with the central limit theorem

Our instructors are experts who make these lessons informative and entertaining through their use of examples, animation and humor. After each lesson, you can assess your learning with a short quiz. There's a comprehensive test at the end of the chapter. If you answer a question incorrectly, the answer key offers links back to the part of the lesson that discusses the question's topic.

NES Math: Sampling Chapter Objectives

All questions on the NES Math test are multiple-choice, and the test is administered by computer. Our lesson quizzes and the chapter exam are also computer-delivered multiple-choice tests, so taking them will give you good experience answering questions in the format you'll find on the NES Math test.

Questions on the NES Math test are divided into five content domains, and questions on sampling are in the Statistics, Probability and Discrete Mathematics content domain. This part of the test accounts for 19% of the total score.

8 Lessons in Chapter 56: NES Math: Sampling
Test your knowledge with a 30-question chapter practice test
What is Random Sampling? - Definition, Conditions & Measures

1. 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.

Simple Random Samples: Definition & Examples

2. Simple Random Samples: Definition & Examples

Simple random sampling is a common method used to collect data in many different fields. From psychology to economics, simple random sampling can be the most feasible way to get information. Learn all about it in this lesson!

Stratified Random Samples: Definition, Characteristics & Examples

3. Stratified Random Samples: Definition, Characteristics & Examples

Random sampling isn't always simple! There are many different types of sampling. In this lesson, you will learn how to use stratified random sampling and when it is most appropriate to use it.

Cluster Random Samples: Definition, Selection & Examples

4. Cluster Random Samples: Definition, Selection & Examples

Cluster random sampling is one of many ways you can collect data. Sometimes it can be confusing knowing which way is best. This lesson explains cluster random sampling, how to use it, and the differences between cluster and stratified sampling.

Systematic Random Samples: Definition, Formula & Advantages

5. 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.

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

6. 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.

Find the Mean & Standard Error of the Sampling Distribution

7. Find the Mean & Standard Error of the Sampling Distribution

Have you ever had a situation where one grade destroyed your average? Wouldn't you like a way of proving that your work was actually pretty good with that one exception? The standard error gives you such a chance.

Finding Probabilities About Means Using the Central Limit Theorem

8. Finding Probabilities About Means Using the Central Limit Theorem

The central limit theorem provides us with a very powerful approach for solving problems involving large amount of data. In this lesson, we'll explore how this is done as well as conditions that make this theorem valid.

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 within the NES Mathematics (304): Practice & Study Guide course

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