Correlation and Regression
Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.
- 4 hours
- 18 Videos
- 58 Exercises
- 39,101 Participants
- 4,200 XP
Create Your Free Account
By continuing you accept the Terms of Use and Privacy Policy, that your data will be stored outside of the EU, and that you are 16 years or older.
Loved by learners at thousands of top companies:
Course Description
Ultimately, data analysis is about understanding relationships among variables. Exploring data with multiple variables requires new, more complex tools, but enables a richer set of comparisons. In this course, you will learn how to describe relationships between two numerical quantities. You will characterize these relationships graphically, in the form of summary statistics, and through simple linear regression models.
-
1
Visualizing two variables
FreeIn this chapter, you will learn techniques for exploring bivariate relationships.
-
Simple linear regression
With the notion of correlation under your belt, we'll now turn our attention to simple linear models in this chapter.
-
Model Fit
In this final chapter, you'll learn how to assess the "fit" of a simple linear regression model.
-
Correlation
This chapter introduces correlation as a means of quantifying bivariate relationships.
-
Interpreting regression models
This chapter looks at how to interpret the coefficients in a regression model.
-
1
Visualizing two variables
FreeIn this chapter, you will learn techniques for exploring bivariate relationships.
-
Correlation
This chapter introduces correlation as a means of quantifying bivariate relationships.
-
Simple linear regression
With the notion of correlation under your belt, we'll now turn our attention to simple linear models in this chapter.
-
Interpreting regression models
This chapter looks at how to interpret the coefficients in a regression model.
-
Model Fit
In this final chapter, you'll learn how to assess the "fit" of a simple linear regression model.
What do other learners have to say?
“I've used other sites, but DataCamp's been the one that I've stuck with.”
Devon Edwards Joseph
Lloyd's Banking Group
“DataCamp is the top resource I recommend for learning data science.”
Louis Maiden
Harvard Business School
“DataCamp is by far my favorite website to learn from.”
Ronald Bowers
Decision Science Analytics @ USAA
Ben Baumer
Assistant Professor at Smith College
Ben is an Assistant Professor in the Statistical & Data Sciences Program at Smith College. He completed his Ph.D. in Mathematics at the Graduate Center of the City University of New York in 2012. He is an Accredited Professional Statistician™ by the American Statistical Association and was previously the Statistical Analyst for the Baseball Operations department of the New York Mets.
See MoreCollaborators
-
Nick Carchedi
-
Tom Jeon