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Lecture
Hypothesis Testing in Statistics
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Related lectures (31)
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Statistical Hypothesis Testing
Covers statistical hypothesis testing, likelihood estimation, and confidence intervals construction.
Understanding Statistics & Experimental Design
Explores unequal variances, replication, power, effect size, biases, and their impact on research outcomes.
Generalized Linear Models
Covers probability, random variables, expectation, GLMs, hypothesis testing, and Bayesian statistics with practical examples.
Likelihood Ratio Tests: Optimality and Applications
Explores the theory and applications of likelihood ratio tests in statistical hypothesis testing.
Linear Regression: Estimation and Testing
Explores linear regression estimation, hypothesis testing, and practical applications in statistics.
Probability and Statistics
Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Hypothesis Testing: Statistics Overview
Provides an overview of hypothesis testing, p-values, Wald test, and non-parametric statistics.
Statistical Hypothesis Testing: Inference and Interpretation
Explores statistical hypothesis testing, including constructing confidence intervals, interpreting p-values, and making decisions based on significance levels.
Statistics & Experimental Design
Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.
Describing Data: Statistics and Hypothesis Testing
Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.
