Copyright

Ch 3: Statistics Overview

About This Chapter

Watch online video lessons to learn about random sampling, frequency tables, standard deviations and more. Each lesson is accompanied by a short multiple-choice quiz to help check your understanding of these statistics topics.

Statistics - Chapter Summary and Learning Objectives

Statistics is the branch of math that deals with the collection and analysis of data. The lessons in this chapter will teach you how to gather samples, calculate averages and create tables. After completing this chapter, you should be able to:

  • Understand the conditions that make a sample random
  • Calculate mean, median, mode and range
  • Interpret standard deviations
  • Find the minimums, maximums and outliers in a data set
  • Create histograms

Video Objective
Descriptive & Inferential Statistics: Definition, Differences & Examples Learn the differences between descriptive and inferential statistics
What's the Difference between Populations & Samples? - Lesson & Quiz Learn the difference between a sample and a population
What is Random Sampling? - Definition, Conditions & Measures Look at the conditions that need to be met for a sample to be random
Simple Random Samples: Definition & Examples Learn how to recognize simple random samples
Stratified Random Samples: Definition, Characteristics & Examples Learn how to recognize stratified random samples
Cluster Random Samples: Definition, Selection & Examples Learn how to recognize cluster random samples
Systematic Random Samples: Definition, Formula & Advantages Learn how to recognize systematic random samples
How to Calculate Mean, Median, Mode & Range Learn how to find the mean, median, mode and range of a data set
Calculating the Mean, Median, Mode & Range: Practice Problems, Lesson & Quiz Practice finding the mean, median, mode and range of a data set
Population & Sample Variance: Definition, Formula & Examples Explore the differences between a population and sample variance
Standard Deviation and Shifts in the Mean Learn how to interpret standard deviation and look at ways a shift in the mean can impact it
Maximums, Minimums & Outliers in a Data Set: Lesson & Quiz Learn how to determine minimums, maximums and outliers in data sets
Quartiles & the Interquartile Range: Definition, Formulate & Examples Learn how to determine quartiles and the interquartile range
Finding Percentiles in a Data Set: Formula, Examples & Quiz Calculate percentiles in a data set
Frequency & Relative Frequency Tables: Definition & Examples Calculate frequency and make relative frequency tables
Cumulative Frequency Tables: Definition, Uses & Examples Learn how to make cumulative frequency tables
How to Calculate Percent Increase with Relative & Cumulative Frequency Tables Use relative and cumulative frequency tables to calculate percent increase
Creating & Interpreting Histograms: Process & Examples Learn how to create and interpret histograms

18 Lessons in Chapter 3: Statistics Overview
Test your knowledge with a 30-question chapter practice test
Descriptive & Inferential Statistics: Definition, Differences & Examples

1. Descriptive & Inferential Statistics: Definition, Differences & Examples

Descriptive and inferential statistics each give different insights into the nature of the data gathered. One alone cannot give the whole picture. Together, they provide a powerful tool for both description and prediction.

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.

Simple Random Samples: Definition & Examples

4. 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

5. 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

6. 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

7. 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.

How to Calculate Mean, Median, Mode & Range

8. How to Calculate Mean, Median, Mode & Range

Measures of central tendency can provide valuable information about a set of data. In this lesson, explore how to calculate the mean, median, mode and range of any given data set.

Calculating the Mean, Median, Mode & Range: Practice Problems

9. Calculating the Mean, Median, Mode & Range: Practice Problems

Calculating the mean, median, mode, and range of a data set is a fundamental part of learning statistics. Use this video to practice your skills and then test your knowledge with a short quiz.

Population & Sample Variance: Definition, Formula & Examples

10. Population & Sample Variance: Definition, Formula & Examples

Population and sample variance can help you describe and analyze data beyond the mean of the data set. In this lesson, learn the differences between population and sample variance.

Calculating the Standard Deviation

11. Calculating the Standard Deviation

In this lesson, we will examine the meaning and process of calculating the standard deviation of a data set. Standard deviation can help to determine if the data set is a normal distribution.

Maximums, Minimums & Outliers in a Data Set

12. Maximums, Minimums & Outliers in a Data Set

When analyzing data sets, the first thing to identify is the maximums, minimums, and outliers. This lesson will help you learn how to identify these important items.

Quartiles & the Interquartile Range: Definition, Formulate & Examples

13. Quartiles & the Interquartile Range: Definition, Formulate & Examples

Quartiles and the interquartile range can be used to group and analyze data sets. In this lesson, learn the definition and steps for finding the quartiles and interquartile range for a given data set.

Finding Percentiles in a Data Set: Formula & Examples

14. Finding Percentiles in a Data Set: Formula & Examples

Percentiles are often used in academics to compare student scores. Finding percentiles in a data set can be a useful way to organize and compare numbers in a data set.

Frequency & Relative Frequency Tables: Definition & Examples

15. Frequency & Relative Frequency Tables: Definition & Examples

Frequency and relative frequency tables are a good way to visualize information. This is especially useful for information that is grouped into categories where you are looking for popularity or mode.

Cumulative Frequency Tables: Definition, Uses & Examples

16. Cumulative Frequency Tables: Definition, Uses & Examples

Cumulative frequency tables can help you analyze and understand large amounts of information. In this lesson, you practice creating and interpreting cumulative frequency tables.

How to Calculate Percent Increase with Relative & Cumulative Frequency Tables

17. How to Calculate Percent Increase with Relative & Cumulative Frequency Tables

In statistics, one way to describe and analyze data is by using frequency tables. This lesson will discuss relative and cumulative frequencies and how to calculate percent increase using these two methods.

Creating & Interpreting Histograms: Process & Examples

18. Creating & Interpreting Histograms: Process & Examples

Creating histograms can help you easily identify and interpret data. This lesson will give you several examples to better understand histograms and how to create them.

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

Earning College Credit

Did you know… We have over 160 college courses that prepare you to earn credit by exam that is accepted by over 1,500 colleges and universities. You can test out of the first two years of college and save thousands off your degree. Anyone can earn credit-by-exam regardless of age or education level.

To learn more, visit our Earning Credit Page

Support