Ch 7: Sampling: Tutoring Solution

About This Chapter

The Sampling chapter of this Statistics 101 Tutoring Solution is a flexible and affordable path to learning about sampling. These simple and fun video lessons are each about five minutes long and they teach all of the sampling principles and methods required in a typical statistics course.

How it works:

  • Begin your assignment or other statistics work.
  • Identify the sampling concepts that you're stuck on.
  • Find fun videos on the topics you need to understand.
  • Press play, watch and learn!
  • Complete the quizzes to test your understanding.
  • As needed, submit a question to one of our instructors for personalized support.

Who's it for?

This chapter of our statistics tutoring solution will benefit any student who is trying to learn sampling and earn better grades. This resource can help students including those who:

  • Struggle with understanding random sampling, the law of large numbers, the central limit theorem or any other sampling topic
  • Have limited time for studying
  • Want a cost effective way to supplement their statistical learning
  • Prefer learning statistics visually
  • Find themselves failing or close to failing their sampling unit
  • Cope with ADD or ADHD
  • Want to get ahead in statistics
  • Don't have access to their statistics teacher outside of class

Why it works:

  • Engaging Tutors: We make learning sampling simple and fun.
  • Cost Efficient: For less than 20% of the cost of a private tutor, you'll have unlimited access 24/7.
  • Consistent High Quality: Unlike a live statistics tutor, these video lessons are thoroughly reviewed.
  • Convenient: Imagine a tutor as portable as your laptop, tablet or smartphone. Learn sampling on the go!
  • Learn at Your Pace: You can pause and rewatch lessons as often as you'd like, until you master the material.

Learning Objectives

  • Define random sampling.
  • Learn how to select different types of random samples, including simple, stratified, cluster and systematic random samples.
  • Become familiar with the law of large numbers.
  • Explain the central limit theorem.
  • Calculate the mean and standard error of a sampling distribution.
  • Use normal distributions and the central limit theorem to find probabilities about means.

9 Lessons in Chapter 7: Sampling: Tutoring Solution
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.

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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