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Ch 2: Summarizing Data: Tutoring Solution

About This Chapter

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

How it works:

  • Begin your assignment or other statistics work.
  • Identify the data summary 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 how to summarize data and earn better grades. This resource can help students including those who:

  • Struggle with understanding mean, median and mode; bimodal and unimodal distributions; data sets; or any other data summary topic
  • Have limited time for studying
  • Want a cost effective way to supplement their statistics learning
  • Prefer learning statistics visually
  • Find themselves failing or close to failing their summarizing data 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 how to summarize data 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 how to summarize data 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

  • Learn how to find the center in a data set.
  • Understand the significance of mean, median, mode and range.
  • Explain how to visually represent a data set.
  • Compare and contrast unimodal and bimodal distributions.
  • Differentiate between mean and median.
  • Describe the concept of spread in a data set.
  • Determine the minimum, maximum and outliers of a data set.
  • Learn how to find percentiles in a data set.
  • Calculate standard deviation.
  • Explain how linear transformations affect measures of center and spread in a data set.
  • Differentiate between population and sample variance.
  • Describe the process for ordering and ranking data.

16 Lessons in Chapter 2: Summarizing Data: Tutoring Solution
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.

What is Numerical Data? - Definition & Examples

16. What is Numerical Data? - Definition & Examples

You will find numerical data in mathematics and in science. Sometimes, it can get confusing to identify. In this lesson, you will learn about numerical data and how it is used.

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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