Ch 37: Michigan Merit Exam - Math: The Normal Distribution

About This Chapter

Watch short and enjoyable video lessons in this chapter that will help you prepare to answer questions about normal distribution for the math section of the Michigan Merit Exam. Evaluate your learning using our quizzes.

Michigan Merit Exam - Math: The Normal Distribution - Chapter Summary

This chapter full of brief video lessons will assist you in your understanding of the process of utilizing the empirical rule. The mixture of our video lessons and quizzes can help you master the following in time for the Michigan Merit Exam:

  • Definition and characteristics of normal distribution
  • Examples and definition of z-scores
  • Areas, estimation, and the normal curve
  • Population percentages and the empirical rule
  • Utilizing normal distribution

After you've finished taking our quizzes, you can view the explanations behind missed questions by clicking the 'Watch Answer' button. You can also read through the video lessons which contain keywords in bold print to let you know the concepts in which you need to focus. If you have any questions, please let our instructors or experts know.

Michigan Merit Exam - Math: The Normal Distribution Objectives

This chapter corresponds to the Statistics & Probability part of the 4-part mathematics section of the Michigan Merit Exam. There are approximately 25 multiple-choice math items. Questions that ask you to display your understanding of statistical data connections and determine z-scores may also be on the exam. The section of the test is normally given on 1 of the 3 testing days.

5 Lessons in Chapter 37: Michigan Merit Exam - Math: The Normal Distribution
Test your knowledge with a 30-question chapter practice test
Normal Distribution: Definition, Properties, Characteristics & Example

1. Normal Distribution: Definition, Properties, Characteristics & Example

In this lesson, we will look at the Normal Distribution, more commonly known as the Bell Curve. We'll look at some of its fascinating properties and learn why it is one of the most important distributions in the study of data.

Finding Z-Scores: Definition & Examples

2. Finding Z-Scores: Definition & Examples

Talking about multiples of standard deviations can get exhausting and confusing. Luckily, z-scores allow us to talk about how far a point is removed from a mean in terms of how many standard deviations away it is.

Estimating Areas Under the Normal Curve Using Z-Scores

3. Estimating Areas Under the Normal Curve Using Z-Scores

So now that we have a Z-score, what is it used for? Sure, it can make your life easier when describing standard deviations, but finding the area under the normal curve is where the Z-score shines.

Estimating Population Percentages from Normal Distributions: The Empirical Rule & Examples

4. Estimating Population Percentages from Normal Distributions: The Empirical Rule & Examples

If you've been working with z-scores for long, you probably get tired of checking those tables every time you need to check the area under the curve. Luckily, the empirical rule helps us memorize the most important values.

Using the Normal Distribution: Practice Problems

5. Using the Normal Distribution: Practice Problems

In this lesson, we will put the normal distribution to work by solving a few practice problems that help us to really master all that the distribution, as well as Z-Scores, have to offer. Review the concepts with a short quiz at the end.

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 Michigan Merit Exam - Math: Test Prep & Practice course

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