  Interactive Course

# Correlation and Regression in R

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

• 4 hours
• 18 Videos
• 58 Exercises
• 48,124 Participants
• 4,200 XP

### 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. 1

#### Visualizing two variables

Free

In this chapter, you will learn techniques for exploring bivariate relationships.

2. #### Simple linear regression

With the notion of correlation under your belt, we'll now turn our attention to simple linear models in this chapter.

3. #### Model Fit

In this final chapter, you'll learn how to assess the "fit" of a simple linear regression model.

4. #### Correlation

This chapter introduces correlation as a means of quantifying bivariate relationships.

5. #### Interpreting regression models

This chapter looks at how to interpret the coefficients in a regression model.

1. 1

#### Visualizing two variables

Free

In this chapter, you will learn techniques for exploring bivariate relationships.

2. #### Correlation

This chapter introduces correlation as a means of quantifying bivariate relationships.

3. #### Simple linear regression

With the notion of correlation under your belt, we'll now turn our attention to simple linear models in this chapter.

4. #### Interpreting regression models

This chapter looks at how to interpret the coefficients in a regression model.

5. #### Model Fit

In this final chapter, you'll learn how to assess the "fit" of a simple linear regression model.

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Lloyd's Banking Group “DataCamp is the top resource I recommend for learning data science.”

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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.

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##### Collaborators
• Nick Carchedi

• Tom Jeon