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Selection mechanisms, colliders, left truncation, inverse probability weighting, Heckman-type correction, nonignorable nonresponse, transportability, and sensitivity analysis for biased samples. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Coverage error, quota and panel designs, attrition, length-biased and Berkson-type selection, healthy-worker effects, weighting limits, and diagnosing bias in observational samples. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Foundations of sampling bias: target populations, sampling frames, convenience and volunteer samples, non-response, survivorship, and limits on generalization. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
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.
Advanced descriptive statistics: Simpson’s paradox in aggregates, robust and transformed summaries, quantiles and winsorization, bivariate association limits, multimodal distributions, and reporting choices. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Intermediate descriptive statistics: variance and standard deviation, IQR and box plots, weighted means, z-scores, correlation as association, and choosing summaries under skew or outliers. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
Foundations of descriptive statistics: measures of center and spread, tables and charts, variable types, and reading summaries without inferential claims. Mix of single-answer and multiple-answer items; multi-select questions ask you to select every correct statement.
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