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Ch 50: ORELA Math: Statistics Overview

About This Chapter

It's likely you'll encounter a number of statistics questions on the ORELA Math assessment. Use the entertaining, quick videos in this chapter to get prepared. If you need additional review after watching the videos, consult their transcripts- they highlight the important concepts.

ORELA Math: Statistics Overview - Chapter Summary

This chapter provides a set of quick, engaging, easy-to-follow videos that explain some of the statistics concepts you need to know for the ORELA Math certification assessment. Lesson topics cover the following:

  • A comparison of descriptive and inferential stats
  • Populations and samples in statistics
  • Parameters and how they differ from stats
  • Quantitative, categorical, discrete and other types of data
  • Using data to judge the strength of a model
  • Experimental vs. observational studies
  • Sampling, random selection and random allocation

If you get hung up anywhere or need our instructors to explain a concept that doesn't make sense, let them know you need assistance. Don't forget to take the lesson quizzes- they provide a great way to practice for the assessment.

Objectives of the ORELA Math: Statistics Overview Chapter

This chapter breaks down the basic statistics concepts you're expected to know for the ORELA certification assessment for math instructors. If you want to see what questions on the ORELA look like, simply refer to our lesson quizzes, which mimic the exam format. You'll have four hours and fifteen minutes to complete the entire 150-question exam.

Questions concerning statistics, probability, and discrete math, including some of the concepts covered in this chapter, make up 19% of the ORELA Math assessment. Accounting for just as much of the test are trigonometry and calculus, math processes and number sense, and measurement and geometry. The final 24% of the exam is devoted to patterns, algebra and functions.

12 Lessons in Chapter 50: ORELA 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.
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 ORELA Mathematics: Practice & Study Guide course

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