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Ch 37: Sampling in Statistics

About This Chapter

Use our video lessons and quizzes to help you understand the use of random sampling in statistics. Study the differences between experiments and observational studies and learn how to estimate parameters.

Sampling in Statistics - Chapter Summary

Bolster your knowledge of statistics terminology with video lessons that can help you differentiate between the parameters used to define an entire population - whether it be a state, a nation or a particular group - and the statistics used to describe the various sample types representing a part of the whole. You can also take a closer look at the random sampling techniques used to ensure every individual has an equal chance at being selected for a sample.

Other lessons allow you to go over the uses of random allocation in experiments once a sample has been determined. Learn how this process differentiates experiments from observational studies, and wrap up your study of statistical sampling with a lesson on the steps involved in estimating a parameter from sample data. This chapter is designed to teach you about the following:

  • Differences between parameters and statistics
  • Differences between populations and samples
  • Conditions and measures of random sampling
  • Befits of random selection and random allocation
  • Definition and characteristics of experiments
  • Examples of observational studies

Let our experienced instructors walk you through these statistics topics and more with entertaining video lessons and transcripts that allow you to work at your own pace and revisit concepts requiring additional study. There are also self-checking, multiple-choice quizzes you can use to chart your progress.

6 Lessons in Chapter 37: Sampling in Statistics
Test your knowledge with a 30-question chapter practice test
Defining the Difference between Parameters & Statistics

1. Defining the Difference between Parameters & Statistics

Using data to describe information can be tricky. The first step is knowing the difference between populations and samples, and then parameters and statistics.

Difference between Populations & Samples in Statistics

2. Difference between Populations & Samples in Statistics

Before you start collecting any information, it is important to understand the differences between population and samples. This lesson will show you how!

What is Random Sampling? - Definition, Conditions & Measures

3. 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.

The Purpose of Statistical Models

4. The Purpose of Statistical Models

Understanding statistics requires that you understand statistical models. This lesson will help you understand the purpose of statistics, statistical models, and types of variables.

Experiments vs Observational Studies: Definition, Differences & Examples

5. Experiments vs Observational Studies: Definition, Differences & Examples

There are different ways to collect data for research. In this lesson, you will learn about collecting data through observational studies and experiments and the differences between each.

Estimating a Parameter from Sample Data: Process & Examples

6. Estimating a Parameter from Sample Data: Process & Examples

One of the most useful things we can do with data is use it to describe a population. Learn how in this lesson as we discuss the concepts of parameters and samples.

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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