Ben is an Assistant Professor in the Program in 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.
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.
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.