Statistical Methodology

MATH 262 is where you learn to reason from data under uncertainty — moving from describing a sample to making defensible claims about the population it came from. The semester walks through probability, sampling distributions, and the Central Limit Theorem, then puts them to work in confidence intervals, hypothesis tests, regression, and categorical analysis, with problem sets and exams that lean on actual computation rather than just theory. It's the applied-stats counterpart to the more proof-heavy probability courses, and for non-math majors taking it as a service course, this is usually the toolkit you'll carry into lab work, theses, and any downstream field that touches real measurements.