About This Chapter
Summarizing Data - Chapter Summary and Learning Objectives
Whether you need to review the processes for ordering and ranking data or the measures used to describe the dispersal of numbers in a data set, this chapter's instructors use plenty of examples, illustrations and sample problems to walk you through each of these concepts. Lessons included here are designed to introduce you to:
- Measures of central tendency
- Distribution shapes
- Measures of statistical spread
- Linear transformations
|What is the Center in a Data Set? - Definition, Lesson & Quiz||Understand the concept of 'center' in a data set.|
|Mean, Median & Mode: Measures of Central Tendency||Learn to differentiate between these measures of central tendency.|
|How to Calculate Mean, Median, Mode & Range||Get examples of mean, median, mode and range. Learn how to calculate these measures.|
|Calculating the Mean, Median, Mode & Range: Practice Problems, Lesson & Quiz||Practice finding the mean, median, mode and range when presented with a data set.|
|Visual Representations of a Data Set: Shape, Symmetry & Skewness||Describe the shape of a set of data using visual representations.|
|Unimodal & Bimodal Distributions: Definition, Examples & Quiz||Learn how to distinguish unimodal distributions from bimodal distributions.|
|The Mean vs. the Median: Differences, Uses, Lesson & Quiz||Understand the differences between the mean and median and know when to use each.|
|Spread in Data Sets: Definition, Example, Lesson & Quiz||Examine the concept of spread in data sets.|
|Maximums, Minimums & Outliers in a Data Set: Lesson & Quiz||Find out how to determine the maximum, minimum and outliers in a data set.|
|Quartiles & the Interquartile Range: Definition, Formulate & Examples||Discover steps for determining quartiles and the interquartile range.|
|Finding Percentiles in a Data Set: Formula, Examples & Quiz||Explore the uses of percentiles and learn how to find these values in a data set.|
|Standard Deviation and Shifts in the Mean||Follow the steps involved in finding the standard deviation. Learn how it can be used to determine a data set's distribution.|
|The Effect of Linear Transformations on Measures of Center & Spread: Lesson & Quiz||Understand what a linear transformation is. Find out how it affects measures of center and spread.|
|Population & Sample Variance: Definition, Formula & Examples||Get tips for finding the variance and learn how to differentiate between population and sample variances.|
|Ordering & Ranking Data: Process, Example, Lesson & Quiz||Explore the processes used to order and rank data.|
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.
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Other chapters within the Statistics 101: Principles of Statistics course