About This Chapter
Fundamentals of Statistics - Chapter Summary
In this chapter, our instructors will help you review several of the equations and processes related to statistics, including descriptive and inferential statistics. You'll cover topics like data gathering for statistic calculation, populations, samples and the organization of statistics in graphs, charts, and tables. Information about data sets will also be reviewed. After completing this chapter, you will have also learned about the following:
- Standard deviation
- Types of statistics
- Mean, median, mode and range
- Standard deviation
- Components of data sets, including quartiles and percentiles
- Minimums, maximums and outliers
- Frequency tables
In addition to the videos included in each lesson, self-assessment quizzes are included, both printable and interactive, that can be used to check your retention of lesson topics. The lessons you complete and the scores you earn can be viewed via the personal dashboard, which tracks your progression through the chapter. Along with other included features, these can help you stay on schedule to complete this chapter and move on to other topics that you want to learn about.
1. Descriptive & Inferential Statistics: Definition, Differences & Examples
Descriptive and inferential statistics each give different insights into the nature of the data gathered. One alone cannot give the whole picture. Together, they provide a powerful tool for both description and prediction.
2. Difference between Populations & Samples in Statistics
Before you start collecting any information, it is important to understand the differences between population and samples. This lesson will show you how!
3. What is Random Sampling? - Definition, Conditions & Measures
Random sampling is used in many research scenarios. In this lesson, you will learn how to use random sampling and find out the benefits and risks of using random samples.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. Frequency & Relative Frequency Tables: Definition & Examples
Frequency and relative frequency tables are a good way to visualize information. This is especially useful for information that is grouped into categories where you are looking for popularity or mode.
11. Cumulative Frequency Tables: Definition, Uses & Examples
Cumulative frequency tables can help you analyze and understand large amounts of information. In this lesson, you practice creating and interpreting cumulative frequency tables.
12. Creating & Interpreting Histograms: Process & Examples
Creating histograms can help you easily identify and interpret data. This lesson will give you several examples to better understand histograms and how to create them.
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