Ch 4: Data Distribution

About This Chapter

Boost your knowledge of data distribution in statistics using this short but effective chapter. These lessons can be referred to if you're looking for supplemental materials for your math class or preparing to take year-end assessment or college placement or entrance exams.

Data Distribution - Chapter Summary

Use this chapter to enhance your understanding of statistical calculations and concepts regarding the distributions of data. Review examples, definitions and processes that explain various methods relating to this topic.

You can also learn more about standard deviation, outliers, box plots, z-scores and more. After successfully completing your study of this chapter, you should be able to do the following:

  • Describe the five-number summary in statistics
  • Create box plots
  • Determine the mean of a group of numbers
  • Calculate the standard deviation of a data set
  • Define and identify outliers
  • Explain the terms center, shape and spread in statistics
  • Describe the characteristics of normal distribution of data and solve relevant practice problems
  • Understand the formula used for z-scores

Video and text lessons offer 24/7 accessibility and expert instruction so you can study when it's most convenient for you and ensure that you fully understand and retain this information. Easily contact instructors with lesson-specific questions and use your Dashboard to track your progress as you move through this chapter. Self-assessment quizzes help you determine the depth of your knowledge and possible need for further review.

10 Lessons in Chapter 4: Data Distribution
Test your knowledge with a 30-question chapter practice test
5 Number Summary in Statistics

1. 5 Number Summary in Statistics

You will learn about the 5 number summary in statistics. This includes finding the median, lower extreme, upper extreme, lower quartile, and upper quartile.

Creating & Interpreting Box Plots: Process & Examples

2. Creating & Interpreting Box Plots: Process & Examples

Box plots are an essential tool in statistical analysis. This lesson will help you create a box plot and understand its meaning. When you are finished, test your understanding with a short quiz!

Mean: Definition & Sample Problems

3. Mean: Definition & Sample Problems

The arithmetic mean of a group of numbers is the technical term for the average of those numbers. This lesson tells you how to compute the mean and shows you how to do it with some real-world examples.

Calculating the Standard Deviation

4. 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.

What are Center, Shape, and Spread?

5. What are Center, Shape, and Spread?

Center, shape, and spread are all words that describe what a particular graph looks like. Watch this video lesson to see how you can identify and explain each.

Outlier in Statistics: Definition & Explanation

6. Outlier in Statistics: Definition & Explanation

An outlier is any value that is numerically distant from most of the other data points in a set of data. Learn about the sources of outliers, histograms, scatterplots, the number line, and more.

Identifying Outliers: Upper Fence & Lower Fence

7. Identifying Outliers: Upper Fence & Lower Fence

Does your research have data that are just too high or too low to be included in a fair review of your data? This lesson gives the steps for finding upper and lower fences to identify outliers.

Normal Distribution of Data: Examples, Definition & Characteristics

8. Normal Distribution of Data: Examples, Definition & Characteristics

In this lesson, we'll explore the normal distribution of data. Learn about the characteristics of normal distribution, how to plot histograms, the empirical rule, and more.

Z-Scores in Statistics Explained: Formula, Overview

9. Z-Scores in Statistics Explained: Formula, Overview

The z-score is the number of standard deviations away from the mean. It allows for standardizing scores so that they can be compared across samples or tests.

Using the Normal Distribution: Practice Problems

10. Using the Normal Distribution: Practice Problems

In this lesson, we will put the normal distribution to work by solving a few practice problems that help us to really master all that the distribution, as well as Z-Scores, have to offer. Review the concepts with a short quiz at the end.

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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