T-statistic

Related lectures (29)

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Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

Covers Analysis of Variance (ANOVA) for assessing categorical variable effects on quantitative outcomes.

Explores qualitative factors in Design of Experiments, including statistical tests and error types.

Explores confidence intervals, hypothesis testing, and ROC curves in statistical analysis.

Covers instrumental variables, addressing endogeneity issues in regression analysis through estimation techniques and practical examples.

Covers the theory of sampling, focusing on statistics for mathematicians.

Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.

Explores copulas for measuring dependence strength in distributions and transforming variables to unit Fréchet margins.

Covers the calculation of paired t-tests, advantages/disadvantages of different t-tests, and the concept of ANOVA.

Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.