Concept

T-statistic

Related lectures (29)

Explores confidence intervals, T-test, and hypothesis testing, including assumptions and critical regions.

Covers the estimation of distributions using samples and probability models.

Explores model checking and residuals in regression analysis, emphasizing the importance of diagnostics for ensuring model validity.

ANOVA: Partitioning Total SS

Covers ANOVA method, focusing on partitioning total sum of squares into treatment and error components, mean square calculations, Fisher statistic, and F-distribution.

Statistical Hypothesis Testing

Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.

Statistics Essentials: The t-test

Introduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.

Confidence Intervals and Hypothesis Tests

Covers confidence intervals, hypothesis tests, standard errors, statistical models, likelihood, Bayesian inference, ROC curve, Pearson statistic, goodness of fit tests, and power of tests.

Bias, Variance, Consistency, EMV

Covers bias, variance, mean squared error, consistency, and maximum likelihood estimation in the Poisson model.

Sampling Theory: Statistics and Inference

Covers sampling theory, statistics, and inference, focusing on the sampling distribution of statistics.

Linear Independence: Covariance and Statistical Dependence

Explores covariance, statistical dependence, education-fertility relationship, hypothesis testing, and comparison statistics for continuous outcomes.

Estimators and Confidence Intervals

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

Analysis of Variance (ANOVA)

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

DOE Qualitative factors: IV

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

Confidence Intervals and Hypothesis Testing

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

Instrumental Variables: Intuition and Estimation

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

Sampling Theory: Statistics for Mathematicians

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

Statistics & Experimental Design

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

Copulas and Extreme Values

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

Statistical Tests: T-Tests and ANOVA

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

Maximum Likelihood Estimation: Multivariate Statistics

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