Ch 50: AEPA Math: Statistics Overview

About This Chapter

If you're in need of some statistics review for the AEPA Mathematics exam, which has been replaced with the NES (National Evaluation Series) Math test, the lessons in this chapter will guide you through all the essentials of the subject. Statistics can be tricky for anyone, even if you've previously mastered it.

AEPA Math: Statistics Overview - Chapter Summary

Use the lessons in this chapter to help you review the essentials of statistics so you're ready for these types of questions on the AEPA Mathematics (NES Mathematics) test. The videos in this chapter have been put together by expert instructors to help you with questions you might encounter on the exam about:

  • Populations and samples and how they differ
  • Estimating a parameter using sample data
  • Different types of data like quantitative, categorical, discrete and continuous
  • Different types of measurements including nominal, ordinal, interval and ratio
  • How experiments and observational studies differ
  • Random selection and random allocation
  • Definition and limitations of convenience sampling

Our expert instructors guide you through these topics, giving you tactics to apply when answering test questions on statistics. The lessons have been made to be short and engaging to keep you focused and make the most efficient use of your time.

12 Lessons in Chapter 50: AEPA Math: Statistics Overview
Test your knowledge with a 30-question chapter practice test
Descriptive & Inferential Statistics: Definition, Differences & Examples

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.

Difference between Populations & Samples in Statistics

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!

Defining the Difference between Parameters & Statistics

3. Defining the Difference between Parameters & Statistics

Using data to describe information can be tricky. The first step is knowing the difference between populations and samples, and then parameters and statistics.

Estimating a Parameter from Sample Data: Process & Examples

4. Estimating a Parameter from Sample Data: Process & Examples

One of the most useful things we can do with data is use it to describe a population. Learn how in this lesson as we discuss the concepts of parameters and samples.

What is Quantitative Data? - Definition & Examples

5. What is Quantitative Data? - Definition & Examples

Watch this video lesson to find out the difference between saying you have seven apples and saying that those apples are delicious. You will learn about quantitative data and why it is useful.

What is Categorical Data? - Definition & Examples

6. What is Categorical Data? - Definition & Examples

Categorical data is one of two types of data that you can collect when conducting research. This lesson will teach you how to understand and use categorical data.

Discrete & Continuous Data: Definition & Examples

7. Discrete & Continuous Data: Definition & Examples

You might be surprised to find that data is more than just a collection of numbers. Data is divided into several categories, including discrete and continuous data. Find out why!

Nominal, Ordinal, Interval & Ratio Measurements: Definition & Examples

8. Nominal, Ordinal, Interval & Ratio Measurements: Definition & Examples

Different types of data can be grouped and measured in different ways. In this lesson, you will learn about nominal, ordinal, interval, and ratio measurements.

The Purpose of Statistical Models

9. The Purpose of Statistical Models

Understanding statistics requires that you understand statistical models. This lesson will help you understand the purpose of statistics, statistical models, and types of variables.

Experiments vs Observational Studies: Definition, Differences & Examples

10. Experiments vs Observational Studies: Definition, Differences & Examples

There are different ways to collect data for research. In this lesson, you will learn about collecting data through observational studies and experiments and the differences between each.

Random Selection & Random Allocation: Differences, Benefits & Examples

11. Random Selection & Random Allocation: Differences, Benefits & Examples

Random selection and random allocation are often confused with one another. This lesson will help you remember the differences between them and learn how to use each method.

Convenience Sampling in Statistics: Definition & Limitations

12. Convenience Sampling in Statistics: Definition & Limitations

Convenience sampling is one of the most common types of sampling in research. This is because of the benefits that convenience sample brings to the researcher. However, there are some limitations. You will learn about both in this lesson.

Chapter Practice Exam
Test your knowledge of this chapter with a 30 question practice chapter exam.
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Practice Final Exam
Test your knowledge of the entire course with a 50 question practice final exam.
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Other Chapters

Other chapters within the AEPA Mathematics (NT304): Practice & Study Guide course

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