Ch 57: AEPA Math: Regression & Correlation

About This Chapter

Use the video lessons in this chapter for a quick and thorough review of regression and correlation as you get ready for the NES Mathematics test, which has taken the place of the AEPA Mathematics test. Our instructor-guided lessons and self-assessment quizzes will help you feel confidently prepared for this test.

AEPA Math: Regression & Correlation - Chapter Summary

Regression and correlation are essential concepts of creating and interpreting graphic representation of statistical data. Understanding how to solve math problems using data correlations will go a long way towards preparation for the test. If you need a refresher on this topic, check out the video lessons in this chapter to prepare for questions about:

  • How to create and interpret scatterplots
  • Definition and formula of simple linear regression
  • Steps to solving problems using linear regression
  • Definition and formula of the correlation coefficient
  • The process of analyzing residuals
  • Differences between correlation and causation
  • Steps to transforming nonlinear data

Our expert instructors have created video lessons that are brief and engaging so you can quickly and effectively review regression and correlation. Short, multiple-choice quizzes follow each lesson to help gauge your comprehension and retention.

7 Lessons in Chapter 57: AEPA Math: Regression & Correlation
Test your knowledge with a 30-question chapter practice test
Creating & Interpreting Scatterplots: Process & Examples

1. 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.

Simple Linear Regression: Definition, Formula & Examples

2. Simple Linear Regression: Definition, Formula & Examples

Simple linear regression is a great way to make observations and interpret data. In this lesson, you will learn to find the regression line of a set of data using a ruler and a graphing calculator.

Problem Solving Using Linear Regression: Steps & Examples

3. Problem Solving Using Linear Regression: Steps & Examples

Linear regression can be a powerful tool for predicting and interpreting information. Learn to use two common formulas for linear regression in this lesson.

Analyzing Residuals: Process & Examples

4. 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

5. 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.

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.

Transforming Nonlinear Data: Steps & Examples

7. Transforming Nonlinear Data: Steps & Examples

Sometimes we have data sets that we need to analyze and interpret, but it's difficult because the data is nonlinear. This lesson will teach you how to transform nonlinear data sets into more linear graphs.

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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Other chapters within the AEPA Mathematics (NT304): Practice & Study Guide course

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