This chapter talks about how we can use a simple linear regression model (SLRM) to understand the relationship between two number-based things. In this model, one of the numbers is the result we want to know more about (X), and the other number helps predict the result (Y). To see if there's a line-like relationship between the two numbers, we first make a scatterplot. This helps us draw a line showing how X and Y are linked. A number called the Pearson correlation coefficient tells us how strong this link is. Using a tool called STATA, the chapter looks at real-world health data to see how this model can help answer questions in public health.