Ch 7: Sampling: Homework Help

About This Chapter

The Sampling chapter of this Statistics Homework Help course helps students complete their sampling homework and earn better grades. This homework help resource uses simple and fun videos that are about five minutes long.

How it works:

  • Identify which concepts are covered on your sampling homework.
  • Find videos on those topics within this chapter.
  • Watch fun videos, pausing and reviewing as needed.
  • Complete sample problems and get instant feedback.
  • Finish your sampling homework with ease!

Topics from your homework you'll be able to complete:

  • Random sampling conditions
  • Simple random samples
  • Cluster random samples
  • Systematic random samples
  • The law of large numbers
  • Sampling distribution
  • The central limit theorem
  • Mean and standard error of a sampling distribution
  • Methods for finding probabilities about means using the central limit theorem

10 Lessons in Chapter 7: Sampling: Homework Help
Test your knowledge with a 30-question chapter practice test
Simple Random Samples: Definition & Examples

1. 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!

What is Random Sampling? - Definition, Conditions & Measures

2. 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.

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.

Understanding the Law of Large Numbers

6. 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

7. 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

8. 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

9. 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.

Chi-Square Test of Independence: Example & Formula

10. Chi-Square Test of Independence: Example & Formula

A chi-square test of independence can be used to calculate and analyze data for differences between observed and expected measurements of categorical data. This lesson provides formulas and examples for use of a chi-square test.

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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