Ch 40: Regression and Correlation

About This Chapter

Use this chapter to learn about regression and correlation in geometry. These video lessons and online quizzes cover several techniques used in describing and analyzing data.

Regression and Correlation - Chapter Summary

The lessons in this chapter provide you with a thorough look at ways to organize and display data. You'll learn how to determine the best way to display data, and get information on using methods such as scatter plots, stem-and-leaf plots, tables and pie charts. Another lesson will show you what correlation is and how to interpret it in research results. You'll explore methods of distinguishing between correlation and causation, and look at the correlation coefficient.

In other lessons, you'll practice using data in interpreting linear relationships. Transforming non-linear data is also explained. By the end of this chapter, you should be informed about topics that include:

  • Creating and interpreting scatter plots
  • Fitting a line with simple linear regression
  • Analyzing residuals
  • Interpreting the slope and intercept of a linear model
  • The correlation coefficient
  • Interpreting correlations in research results
  • Interpreting linear relationships using data

These brief, engaging geometry videos are presented by experienced instructors who use real life examples to illustrate their topics. Practice lessons allow you to test your knowledge of what's been covered, and all these lessons have multiple-choice quizzes at the end. The questions in the quizzes link back to the videos, allowing you to review important concepts and passages. There's also a complete written transcript of every video lesson, which allows you to read through the lesson in addition to watching the video.

12 Lessons in Chapter 40: Regression and Correlation
Test your knowledge with a 30-question chapter practice test
Making Arguments & Predictions from Univariate Data

1. Making Arguments & Predictions from Univariate Data

Univariate data is used to describe a situation or experiment; however, you can also use the data to make arguments and predictions. This lesson will show you how to use measures of central tendency to make arguments and predictions.

What is Bivariate Data? - Definition & Examples

2. 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

3. 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

4. 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

5. 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

6. 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.

Interpreting the Slope & Intercept of a Linear Model

7. Interpreting the Slope & Intercept of a Linear Model

You've probably seen slope and intercept in algebra. These concepts can also be used to predict and understand information in statistics. Take a look at this lesson!

The Correlation Coefficient: Definition, Formula & Example

8. 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

9. 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

10. 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

11. 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!

Transforming Nonlinear Data: Steps & Examples

12. 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.
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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