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Advanced inferential statistics: likelihood and MLE intuition, bootstrap, permutation tests, Bayesian vs frequentist contrasts, mixed models, nonparametrics, Simpson’s paradox in inference, and critique of p-hacking. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Intermediate inferential statistics: power and sample size, multiple comparisons, ANOVA intuition, chi-square tests, paired designs, assumption diagnostics, and interpreting CIs vs tests. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Foundations of inferential statistics: populations vs samples, estimation, confidence intervals, hypothesis testing basics, p-values, and common test families. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
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