About This Chapter
Bivariate Relationships in Statistics - Chapter Summary
In these lessons, our professional instructors will help you improve your understanding of bivariate relationships and the statistics used to evaluate them. Follow along with our instructors to review the uses of scatter plots as well as the calculations for correlations and linear regressions. After this chapter you should be able to answer questions about:
- The definition of bivariate data
- Uses of scatterplots and line graphs
- Processes of creating scatterplots
- Formulas and interpretations of Pearson correlations
- Differences between correlation and causation
- What a regression analysis is
- Formulas for simple linear regressions
- Steps for using linear regressions to solve problems
After these lessons, use the lesson transcripts to fortify your retention of the information presented in them and study the key terms and concepts. Take the lesson quizzes to identify the topics you don't understand, and use the video tags to return to and review the parts of the lessons that explain these topics. If you come across a topic that confuses you, use the 'teacher' tabs of the lessons to ask our instructors for assistance.
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.
2. The Relationship Between Variables: Correlation Coefficient & Scatterplots
The focus of this lesson is on how both correlation coefficients and scatterplots convey the same message. Specifically, this lesson will explore how these two can reveal the same information but in different ways.
3. Scatterplot and Correlation: Definition, Example & Analysis
A scatterplot is used to graphically represent the relationship between two variables. Explore the relationship between scatterplots and correlations, the different types of correlations, how to interpret scatterplots, and more.
4. Scatterplots and Line Graphs: Definitions and Uses
After watching this video, you will be able to understand scatter plots and line graphs. You will also be able to use them to tell people a story about what you see and observe. You will also be able to read them.
5. 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.
6. Pearson Correlation Coefficient: Formula, Example & Significance
The Pearson correlation coefficient is just one of many types of coefficients in the field of statistics. The following lesson provides the formula, examples of when the coefficient is used, its significance, and a quiz to assess your knowledge of the topic.
7. 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.
8. Interpreting the Correlation Coefficient
This lesson explains the process of interpreting and analyzing a correlation coefficient both as a figure and as a context by discussing common and easy to understand examples.
9. 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.
10. 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.
11. Regression Analysis: Definition & Examples
Watch this video lesson to learn about regression analysis and how you can use it to help you analyze and better understand data that you receive from surveys or observations. Learn what is involved in regression analysis and what to look out for.
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