In this chapter we study relationships between two columns of the data matrix which contain observations on quantitative random variables. The first section of the chapter will be devoted to a review of theory for bivariate distributions for both discrete and continuous random variables. This section will also include an introduction to the theory of correlation and regression and an introduction to the bivariate normal distribution. The second and third sections of the chapter will be devoted to the techniques of inference for correlation and regression respectively. The last section of the chapter will discuss bivariate inference in the presence of other variables including the topics of partial correlation and lurking variables. In each of the four sections a review of techniques normally presented in an introductory course will be combined with additional material.