You’ve computed regression slopes, run t‑tests, and interpreted p‑values. But what makes those standard errors trustworthy? This chapter takes you behind the scenes — first into large‑sample approximations that let us make reliable conclusions without assuming the errors follow a specific shape, and then into exact results that hold under ideal, classical conditions. By the end, you’ll see both the “why” and the “when” of regression inference.