Fundamental principles of statistical learning and inference for data science Understanding of types of analytics, probability, variability, relationship between variables, probability distributions, law of large numbers, Central Limit Theorem, hypothesis testing and statistical significance, and elementary theory of regression. Prerequisite: MATH 281 or STAT 265. Students presenting STAT 265 must also present one of MATH 117 or MATH 216 as corequisite. Credit can only be obtained in one of STAT 266 or STAT 276.