Ch 2: Summarizing Data: Help and Review

About This Chapter

The Summarizing Data chapter of this College-Level Principles of Statistics Help and Review course is the simplest way to master summarizing data. This chapter uses simple and fun videos that are about five minutes long, plus lesson quizzes and a chapter exam to ensure students learn the essentials of summarizing data.

Who's it for?

Anyone who needs help learning or mastering college statistics material will benefit from taking this course. There is no faster or easier way to learn college statistics. Among those who would benefit are:

  • Students who have fallen behind in understanding data sets or working with mean, median and mode
  • Students who struggle with learning disabilities or learning differences, including autism and ADHD
  • Students who prefer multiple ways of learning math (visual or auditory)
  • Students who have missed class time and need to catch up
  • Students who need an efficient way to learn about summarizing data
  • Students who struggle to understand their teachers
  • Students who attend schools without extra math learning resources

How it works:

  • Find videos in our course that cover what you need to learn or review.
  • Press play and watch the video lesson.
  • Refer to the video transcripts to reinforce your learning.
  • Test your understanding of each lesson with short quizzes.
  • Verify you're ready by completing the Summarizing Data chapter exam.

Why it works:

  • Study Efficiently: Skip what you know; review what you don't.
  • Retain What You Learn: Engaging animations and real-life examples make topics easy to grasp.
  • Be Ready on Test Day: Use the Summarizing Data chapter exam to be prepared.
  • Get Extra Support: Ask our subject-matter experts any summarizing data question. They're here to help!
  • Study With Flexibility: Watch videos on any web-ready device.

Students will review:

This chapter helps students review the concepts in a Summarizing Data unit of a standard college statistics course. Topics covered include:

  • Calculating the mean, median, mode and range
  • Visual representations of a data set
  • Unimodal and bimodal distributions
  • Quartiles and the interquartile range
  • Standard deviation and shifts in the mean

19 Lessons in Chapter 2: Summarizing Data: Help and Review
Test your knowledge with a 30-question chapter practice test
What is the Center in a Data Set? - Definition & Options

1. What is the Center in a Data Set? - Definition & Options

Finding the center in a data set can sometimes be a little confusing. This lesson will help you determine the correct method for finding the center in a data set, and when you are finished, test your knowledge with a short quiz!

Mean, Median & Mode: Measures of Central Tendency

2. Mean, Median & Mode: Measures of Central Tendency

By describing the data using central tendency, a researcher and reader can understand what the typical score looks like. In this lesson, we will explore in more detail these measures of central tendency and how they relate to samples and populations.

How to Calculate Mean, Median, Mode & Range

3. 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

4. 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.

Visual Representations of a Data Set: Shape, Symmetry & Skewness

5. Visual Representations of a Data Set: Shape, Symmetry & Skewness

Visual representations are a fantastic way of understanding and analyzing your data. Use this lesson to understand the characteristics of visual representations of data.

Unimodal & Bimodal Distributions: Definition & Examples

6. Unimodal & Bimodal Distributions: Definition & Examples

Sometimes a single mode does not accurately describe a data set. In this lesson, learn the differences between and the uses of unimodal and bimodal distribution. When you are finished, test your knowledge with a quiz!

The Mean vs the Median: Differences & Uses

7. The Mean vs the Median: Differences & Uses

Most people can find the mean and the median of a data set, but do you know when to use the mean and when to use the median to describe the information?

Spread in Data Sets: Definition & Example

8. Spread in Data Sets: Definition & Example

Identifying the spread in data sets is a very important part of statistics. You can do this several ways, but the most common methods are through range, interquartile range, and variance.

Maximums, Minimums & Outliers in a Data Set

9. 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

10. 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

11. 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.

Calculating the Standard Deviation

12. 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.

The Effect of Linear Transformations on Measures of Center & Spread

13. The Effect of Linear Transformations on Measures of Center & Spread

Linear transformations can be a great way to manipulate and analyze data. This lesson will show you how those transformations affect the center and spread of data.

Population & Sample Variance: Definition, Formula & Examples

14. 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.

Ordering & Ranking Data: Process & Example

15. Ordering & Ranking Data: Process & Example

Ordering and ranking data can often be more important than you might think. In addition to being an important part of competitions, ranking data can be another way of analyzing and evaluating research.

Sample Space in Statistics: Definition & Examples

16. Sample Space in Statistics: Definition & Examples

In this lesson, you will learn the definition of sample space - an important concept in the study of probability. Examples and quiz questions will illustrate how this concept exists in the real world.

X-Bar in Statistics: Theory & Formula

17. X-Bar in Statistics: Theory & Formula

A cow visits an x-bar to give the bartender samples of milk. The bartender asks the cow, 'What is the mean of this milk?' The cow replies, 'Trying to esti-mate mu!' This lesson explains x-bars and their role in estimating parameters.

Finding the 40th Percentile

18. Finding the 40th Percentile

Newspapers and news programs are often citing percentiles when they report on elections, social trends, and other factors that affect the population. This lesson goes over a step by step process for determining the 40th percentile.

Median Absolute Deviation: Formula & Examples

19. Median Absolute Deviation: Formula & Examples

Measures of deviation are commonly quoted when referring to data. In this lesson, we look at the median absolute deviation, showing how it is calculated and why it is insensitive to outliers.

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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