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Ch 50: NES Math: Statistics Overview

About This Chapter

Let us assist you in reviewing information on ways to analyze and utilize statistics as you get ready to take the NES Math exam. We offer informative videos and short quizzes to prepare you for this section of the exam.

NES Math: Statistics Overview - Chapter Summary

Use the lessons in this chapter to refresh your knowledge of how to categorize and analyze statistical data. Our videos, quizzes and other study tools can help you answer NES Math exam questions on topics including:

  • Descriptive and inferential statistics
  • Differences between populations and samples and between parameters and statistics
  • Definitions of quantitative and categorical data
  • Discrete and continuous data
  • Nominal, ordinal, ratio and interval measurements
  • How to measure a model's strength with gathered data
  • Differences in random selection and random allocation
  • Applications and limitations of convenience sampling

Our instructors have developed informative and entertaining lessons to help you prepare for the NES Math exam. You can use the clickable timeline in each video to jump to specific parts of the lesson for review. A personalized Dashboard feature can aid you in keeping up with your progress through the lessons and quizzes in this chapter.

NES Math: Statistics Overview - Chapter Objectives

At least five states use the NES Math exam as one of the requirements for obtaining certification to teach mathematics at the secondary level. The exam's 150 questions are grouped into content domains, and the questions on statistics are in the Statistics, Probability and Discrete Mathematics section, which makes up 19% of the total score.

Because all questions on the NES Math exam are multiple-choice, our lesson quizzes and chapter test offer good practice because they are in the same format. These short tests also show you where extra study is required.

12 Lessons in Chapter 50: NES Math: Statistics Overview
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.

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Other Chapters

Other chapters within the NES Mathematics (304): Practice & Study Guide course

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