Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.
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.
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.
In this chapter, you will learn techniques for exploring bivariate relationships.
With the notion of correlation under your belt, we'll now turn our attention to simple linear models in this chapter.
In this final chapter, you'll learn how to assess the "fit" of a simple linear regression model.
This chapter introduces correlation as a means of quantifying bivariate relationships.
This chapter looks at how to interpret the coefficients in a regression model.
In this chapter, you will learn techniques for exploring bivariate relationships.
This chapter introduces correlation as a means of quantifying bivariate relationships.
With the notion of correlation under your belt, we'll now turn our attention to simple linear models in this chapter.
This chapter looks at how to interpret the coefficients in a regression model.
In this final chapter, you'll learn how to assess the "fit" of a simple linear regression model.
“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