Statistical inference is used to describe procedures that draw conclusions from datasets arising from systems affected by random variation.This subject comprises components in estimation and testing hypotheses. Topics in the first component include method of moments and maximum likelihood, reduction by sufficiency and invariance, unbiasedness, consistency, efficiency and robustness. The second component examines size and power of tests, Neyman-Pearson lemma, optimality of tests, the likelihood ratio test and relationship to confidence interval estimation. This subject is co-taught with STA3SI. For STA4SI there is greater emphasis on research and inquiry with an expactation that students independently formulate proofs for extension questions related to the subject material.

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