4.4 Line-fitting/regression

Instead of thinking locally and producing estimates of the mean of 𝑌 conditional on values of 𝑋, we can assume that the underlying relationship between 𝑌 and 𝑋 can be represented by some sort of shape. In basic forms of regression, that shape is a straight line.

• can describe relationship for missing data
• clear: positive/negative
• results are more precise since using all data
• ☹ line – have to pick shape of line
  • OLS: use linear/squared/log, but with linear coefficient
  • no OLS: different function
• Other option: Pearson correlation coefficient
  • Nice to interpret: between -1 and 1