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Lecture
Introduction to t tests
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Related lectures (30)
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Statistical Hypothesis Testing: Inference and Interpretation
Explores statistical hypothesis testing, including constructing confidence intervals, interpreting p-values, and making decisions based on significance levels.
Statistical Hypothesis Testing
Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.
Z-Test: Hypothesis Testing
Introduces hypothesis testing, focusing on the Z-test and critical regions.
Statistical Tests: T-Tests and ANOVA
Covers the calculation of paired t-tests, advantages/disadvantages of different t-tests, and the concept of ANOVA.
Hypothesis Testing: State of Nature
Explores hypothesis testing, emphasizing the state of nature and the importance of choosing the most powerful test.
Statistical Modeling: Estimation and Hypothesis Testing
Covers statistical modeling, estimation, CLT, confidence intervals, and hypothesis testing steps with practical examples.
Bayesian Statistics: Hypothesis Testing and Estimation
Covers hypothesis testing, p-values, significance levels, and Bayesian estimation.
Testing: t-tests
Covers t-tests, p-values calculation, and comparison of coefficients.
T-tests and Empirical Tests
Explores t-tests, z-tests, and empirical tests for sample comparison and hypothesis testing.
Chi-Square Test: Independence Hypothesis
Explains the Chi-Square test for independence hypothesis and its practical applications.
