About This Chapter
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
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!
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.
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.
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.
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.
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!
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?
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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Other chapters within the Introduction to Statistics: Help and Review course
- Overview of Statistics: Help and Review
- Tables and Plots: Help and Review
- Probability: Help and Review
- Discrete Probability Distributions: Help and Review
- Continuous Probability Distributions: Help and Review
- Sampling: Help and Review
- Regression & Correlation: Help and Review
- Hypothesis Testing in Statistics