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Ch 37: NYSTCE Mathematics: Regression & Correlation

About This Chapter

Let the lessons in our Regression & Correlation chapter sharpen your skills in data analysis. Use the information, practice problems and quizzes to help you prepare for the questions you may expect to find on the NYSTCE Mathematics test.

NYSTCE Mathematics: Regression & Correlation - Chapter Summary

Data collection and analysis is a fundamental part of conducting many types of research in a variety of disciplines. Learn more about the topic in anticipation of passing the NYSTCE Mathematics exam. These lessons will help you brush up on data organization and interpretation by providing practice in the following areas:

  • Developing and reading scatterplots
  • Finding the regression line in a set of data, practice problems
  • Explanation and formula for the correlation coefficient
  • Understanding correlations in scientific research
  • Differentiating between causation and correlation
  • How to use data to interpret linear relationships
  • Using nonlinear regression models to analyze data

Gain fluency and confidence as you work through these quick yet informative video lessons. The quizzes provide practice and reinforcement, while the chapter tests allow you to check your mastery of the material overall. Bright, lively writing and skilled presentation make the videos fun to watch and easy to follow, and access to our instructors ensures that your questions will be answered upon request.

8 Lessons in Chapter 37: NYSTCE Mathematics: 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.

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.

Interpreting Linear Relationships Using Data: Practice Problems

7. Interpreting Linear Relationships Using Data: Practice Problems

Understanding linear relationships is an important part of understanding statistics. This lesson will help you review linear relationships and will go through three practice problems to help you retain your knowledge. When you are finished, test out your knowledge with a short quiz!

Analyzing Data With Nonlinear Regression Models

8. Analyzing Data With Nonlinear Regression Models

There are many nonlinear regression models that can be used to solve a variety of real-world problems. Data in finance, business and physical science can be analyzed using nonlinear regression functions.

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 NYSTCE Mathematics (004): Practice & Study Guide course

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