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Ch 35: Michigan Merit Exam - Math: Creating & Interpreting Plots

About This Chapter

In this chapter, you will find short and amusing video lessons and quizzes about the creation of plots that will help you prepare for the math section of the Michigan Merit Exam. These study resources will help you get the practice you need answering questions similar to the ones you will see on exam day.

Michigan Merit Exam - Math: Creating & Interpreting Plots - Chapter Summary

Watch interesting video lessons about the definition of cumulative frequency tables and data sets. Take an end of the lesson quiz about how to understand the information on a leaf display. This Creating and Interpreting Plots chapter will enable you to answer questions about the following:

  • Definition of relative frequency, frequency, and cumulative frequency tables
  • Creation of stem displays, leaf displays, and histograms
  • Examples of frequency polygons, dot plots, and box plots
  • Descriptions of data sets
  • Definition of unimodal and bimodal distributions

While you are viewing the video lessons, you can jump to specific topics by using the timeline. You can find the explanations for correct quiz answers by clicking the 'Watch Answer' buttons. Video transcripts are also available if you would like to read them. They contain bold printed keywords that make you aware of the words in which you need to focus. Please let our instructors or experts know if you have any questions

Michigan Merit Exam - Math: Creating & Interpreting Plots Objectives

This chapters study guides relate to the Statistics and Probability section of the 4-part math portion of the Michigan Merit Exam. You may be asked to identify the correct plots for data and to make histograms and other plots. You can expect to answer a total of 25 multiple-choice math questions on your exam.

9 Lessons in Chapter 35: Michigan Merit Exam - Math: Creating & Interpreting Plots
Test your knowledge with a 30-question chapter practice test
Frequency & Relative Frequency Tables: Definition & Examples

1. Frequency & Relative Frequency Tables: Definition & Examples

Frequency and relative frequency tables are a good way to visualize information. This is especially useful for information that is grouped into categories where you are looking for popularity or mode.

Cumulative Frequency Tables: Definition, Uses & Examples

2. Cumulative Frequency Tables: Definition, Uses & Examples

Cumulative frequency tables can help you analyze and understand large amounts of information. In this lesson, you practice creating and interpreting cumulative frequency tables.

Creating & Reading Stem & Leaf Displays

3. Creating & Reading Stem & Leaf Displays

Every once in a while you will come across stem-and-leaf displays in statistics. These displays can be very useful in identifying all of the values in a data set while still visually representing the data.

Creating & Interpreting Histograms: Process & Examples

4. Creating & Interpreting Histograms: Process & Examples

Creating histograms can help you easily identify and interpret data. This lesson will give you several examples to better understand histograms and how to create them.

Creating & Interpreting Frequency Polygons: Process & Examples

5. Creating & Interpreting Frequency Polygons: Process & Examples

Frequency polygons can be used to analyze data sets in many different ways. They are also a great way to visualize and compare two sets of data. In this lesson, learn the uses and create a frequency polygon.

Creating & Interpreting Dot Plots: Process & Examples

6. Creating & Interpreting Dot Plots: Process & Examples

Dot plots are a visual way to display the frequency distribution in a data set. In this lesson, you will learn how to construct a dot plot and understand its uses.

Creating & Interpreting Box Plots: Process & Examples

7. Creating & Interpreting Box Plots: Process & Examples

Box plots are an essential tool in statistical analysis. This lesson will help you create a box plot and understand its meaning. When you are finished, test your understanding with a short quiz!

Visual Representations of a Data Set: Shape, Symmetry & Skewness

8. Visual Representations of a Data Set: Shape, Symmetry & Skewness

Visual representations are a fantastic way of understanding and analyzing your data. Use this lesson to understand the characteristics of visual representations of data.

Unimodal & Bimodal Distributions: Definition & Examples

9. Unimodal & Bimodal Distributions: Definition & Examples

Sometimes a single mode does not accurately describe a data set. In this lesson, learn the differences between and the uses of unimodal and bimodal distribution. When you are finished, test your knowledge with a quiz!

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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