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Lecture
Understanding Statistics & Experimental Design
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Related lectures (31)
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Statistical Hypothesis Testing
Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.
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.
Understanding Statistics & Experimental Design
Covers basic probability theory, signal detection theory, statistics, and meta-statistics, explaining effect sizes, power, and hypothesis testing.
Statistical Inference
Covers likelihood ratio statistic, confidence intervals, and hypothesis testing concepts.
Confidence Intervals and T-Test
Explores confidence intervals, T-test, and hypothesis testing, including assumptions and critical regions.
Statistical Modeling: Estimation and Hypothesis Testing
Covers statistical modeling, estimation, CLT, confidence intervals, and hypothesis testing steps with practical examples.
Understanding Statistics & Experimental Design
Explores unequal variances, replication, power, effect size, biases, and their impact on research outcomes.
Distribution Theory of Least Squares
Explores the distribution theory of least squares estimators in a Gaussian linear model, focusing on precision and confidence intervals construction.
Confidence Intervals and Hypothesis Testing
Explores confidence intervals, hypothesis testing, and ROC curves in statistical analysis.
Chi-Square Test: Independence Hypothesis
Explains the Chi-Square test for independence hypothesis and its practical applications.
