BiteSize Stats: Hypothesis Testing for Single Samples

О курсе

BiteSize Statistics for Business: Hypothesis Testing for Single Samples is the first course in the BiteSize Stats for Business specialization. It moves from probability theory to inferential statistics: given one sample, how do you rigorously test a claim about the population it came from — and how confident should you be in the answer? Across five modules, learners progress from the logic of hypothesis testing (hypotheses, error types, p-values, decision rules), through one-sample Z-tests and t-tests for means and proportions with their matching confidence intervals, to the chi-square goodness-of-fit test for categorical data, and finally statistical power, effect size, and sample size planning. Every core lesson pairs a focused reading with a hands-on interactive notebook built around a realistic business scenario, and every module includes a fully worked demo case study and an ungraded practice project applying the module's tools to a new scenario.

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Di Wu

Instructor