Ch 52: AEPA Middle Grades Math: Samples & Populations

About This Chapter

This chapter explores statistical sampling and populations and is a great review when preparing for the AEPA Middle Grades Mathematics exam for teacher certification in Arizona. Want to make sure you have mastered the material? Take the short quiz at the end of each lesson!

AEPA Middle Grades Math: Samples & Populations - Chapter Summary

An understanding of research and sampling is important when reviewing for the statistics portion of this AEPA exam. From random sampling to variance, the lessons in this chapter will help you review sampling and populations. After completing the material in this chapter, you should understand:

  • Samples and populations in research
  • Random, convenience, probability and non-probability sampling
  • Random assignment, selection and allocation
  • Interpreting randomized experiments
  • Population, sample and generalizability
  • Comparing parameters and statistics
  • Estimating parameters from sample data

Use our engaging lessons and self-assessment quizzes to make the most of your study time as you prepare for this AEPA exam. Our videos have embedded tags making it easy to find your topic, and the lesson transcript is ideal for quick look-ups. Have a question? No problem, our subject experts are standing by to help.

Objectives of the AEPA Middle Grades Math: Samples & Populations Chapter

The AEPA Middle Grades Mathematics exam assesses your math knowledge in a number of areas. The material covered in this Samples and Populations chapter is from the Statistics, Probability and Discrete Mathematics domain, which makes up approximately one quarter of the test, or about 38 questions.

The AEPA Middle Grades Mathematics exam is a computer-based test (CBT). The self-assessment quizzes in the chapter are an excellent way to familiarize yourself with the computer-based format. There are 150 multiple-choice questions and a four hour and fifteen minute time limit.

10 Lessons in Chapter 52: AEPA Middle Grades Math: Samples & Populations
Test your knowledge with a 30-question chapter practice test
Samples & Populations in Research: Definition

1. Samples & Populations in Research: Definition

When planning an experiment, you will likely use groups of participants. This lesson explores the types of groups an experimenter can collect data from and the reason why there are different groups.

What is Random Sampling? - Definition, Conditions & Measures

2. 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.

Non-Probability Sampling Methods: Definition & Types

3. Non-Probability Sampling Methods: Definition & Types

There are many different ways to choose a sample for a research study. In this lesson, we'll look at three types of non-probability sampling: convenience, quota, and judgmental (or purposive sampling) and when to use each type.

Issues in Probability & Non-Probability Sampling

4. Issues in Probability & Non-Probability Sampling

Choosing a sample is an important part of research. The two methods of sampling both come with their own set of issues. In this lesson, we'll look at the issues with probability and non-probability sampling.

Random Assignment in Research: Definition and Importance

5. Random Assignment in Research: Definition and Importance

In order to get the most accurate results, researchers must choose and assign their subjects in a random manner. In this lesson, we'll look at random assignment, random selection, and why they are important.

Random Selection & Random Allocation: Differences, Benefits & Examples

6. 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.

Analyzing & Interpreting the Results of Randomized Experiments

7. Analyzing & Interpreting the Results of Randomized Experiments

Analyzing and interpreting the results of an experiment can be a confusing process, and it's easy to make mistakes. This lesson will help you understand the important factors of experiment analysis.

Population & Sample Variance: Definition, Formula & Examples

8. 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.

Defining the Difference between Parameters & Statistics

9. 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

10. 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.

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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Other Chapters

Other chapters within the AEPA Middle Grades Mathematics (NT203): Practice & Study Guide course

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