Ch 8: Regression & Correlation: Help and Review
About This Chapter
Who's it for?
Anyone who needs help learning or mastering college statistics material will benefit from taking this course. There is no faster or easier way to learn college statistics. Among those who would benefit are:
- Students who have fallen behind in understanding simple linear regression or working with scatterplots
- Students who struggle with learning disabilities or learning differences, including autism and ADHD
- Students who prefer multiple ways of learning math (visual or auditory)
- Students who have missed class time and need to catch up
- Students who need an efficient way to learn about regression and correlation
- Students who struggle to understand their teachers
- Students who attend schools without extra math learning resources
How it works:
- Find videos in our course that cover what you need to learn or review.
- Press play and watch the video lesson.
- Refer to the video transcripts to reinforce your learning.
- Test your understanding of each lesson with short quizzes.
- Verify you're ready by completing the Regression and Correlation chapter exam.
Why it works:
- Study Efficiently: Skip what you know; review what you don't.
- Retain What You Learn: Engaging animations and real-life examples make topics easy to grasp.
- Be Ready on Test Day: Use the Regression and Correlation chapter exam to be prepared.
- Get Extra Support: Ask our subject-matter experts any regression and correlation question. They're here to help!
- Study With Flexibility: Watch videos on any web-ready device.
Students will review:
This chapter helps students review the concepts in a Regression and Correlation unit of a standard college statistics course. Topics covered include:
- Creating and interpreting scatter plots
- Simple linear regression
- Interpreting the slope and intercept of a linear model
- How to interpret correlations in research results
- Correlation vs. causation
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.
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.
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.
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.
5. 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!
6. 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.
7. 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.
8. 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.
9. 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!
10. 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.
11. Coefficient of Determination: Definition, Formula & Example
The coefficient of determination is an important quantity obtained from regression analysis. In this lesson, we will show how this quantity is derived from linear regression analysis, and subsequently demonstrate how to compute it in an example.
12. Scatter Diagram: Definition & Examples
Scatter diagrams? What are those all about? Who uses them? Find out the answers to these questions and how scatter diagrams can be used to represent real world data.
13. Correlation: Definition, Analysis & Examples
Correlation describes the relationship between two sets of data. In this lesson, we'll delve into what correlation is and the different types of correlation that can be encountered.
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Other Chapters
Other chapters within the Introduction to Statistics: Help and Review course
- Overview of Statistics: Help and Review
- Summarizing Data: Help and Review
- Tables and Plots: Help and Review
- Probability: Help and Review
- Discrete Probability Distributions: Help and Review
- Continuous Probability Distributions: Help and Review
- Sampling: Help and Review
- Hypothesis Testing in Statistics
