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Ch 38: Michigan Merit Exam - Math: Scatterplots & Correlation

About This Chapter

You have chosen the perfect test preparation website to assist you with the topic of scatterplots and correlation. Our chapter of short and interesting lessons and quizzes will help you get practice in the areas needed to pass your test.

Michigan Merit Exam - Math: Scatterplots & Correlation - Chapter Summary

Prepare for your exam by watching these quick video lessons about bivariate data. Take our quizzes to see if you are knowledgeable about the process of determining the correlation coefficient. The mix of video lessons and quizzes will reassure you that you are prepared to answer questions based on the following items:

  • Examples and definition of bivariate data
  • Construction and reading of a scatterplot
  • Analysis of residuals
  • Definition, makeup, and examples of the correlation coefficient
  • Ways of understanding research correlations
  • Causation and correlation

When you move through the videos, you will notice that you can use the timeline to jump back and forth to topics. If you need explanations for the correct answers of missed quiz questions, you can click the 'Watch Answer' button to go to the relevant parts of the videos. Do not hesitate to let our experts know if you have a question. They are only a few clicks away.

Michigan Merit Exam - Math: Scatterplots & Correlation Objectives

This chapter of study guides relates directly to the Statistics and Probability section of the Michigan Merit Exam. The section is equal to 1 part of the 4-part mathematics section. There are approximately 25 multiple-choice math questions in all. Please remember that you could also be tested on your understanding of the different types and purpose of correlations.

6 Lessons in Chapter 38: Michigan Merit Exam - Math: Scatterplots & Correlation
Test your knowledge with a 30-question chapter practice test
What is Bivariate Data? - Definition & Examples

1. What is Bivariate Data? - Definition & Examples

In this lesson, you will be learning about the definition and uses of bivariate data. We will also compare and contrast the characteristics of univariate data and bivariate data.

Creating & Interpreting Scatterplots: Process & Examples

2. Creating & Interpreting Scatterplots: Process & Examples

Scatterplots are a great visual representation of two sets of data. In this lesson, you will learn how to interpret bivariate data to create scatterplots and understand the relationship between the two variables.

Analyzing Residuals: Process & Examples

3. Analyzing Residuals: Process & Examples

Can you tell what's normal or independent and what's not? Sometimes, we need to figure this out in the world of statistics. This lesson shows you how as it explains residuals and regression assumptions in the context of linear regression analysis.

The Correlation Coefficient: Definition, Formula & Example

4. The Correlation Coefficient: Definition, Formula & Example

The correlation coefficient is an equation that is used to determine the strength of the relationship between two variables. This lesson helps you understand it by breaking the equation down.

How to Interpret Correlations in Research Results

5. How to Interpret Correlations in Research Results

Perhaps the most common statistic you'll see from psychology is a correlation. Do you know how to correctly interpret correlations when you see them? This lesson covers everything you need to know.

Correlation vs. Causation: Differences & Definition

6. Correlation vs. Causation: Differences & Definition

When conducting experiments and analyzing data, many people often confuse the concepts of correlation and causation. In this lesson, you will learn the differences between the two and how to identify one over the other.

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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