Sample size determination

Formal sciences
Statistics
Statistical inference
Mathematical statistics

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Related lectures (31)

Page 1 of 4

Normal Distribution: Characteristics and Z-scores

Explores normal distribution characteristics, Z-scores, probability in inferential statistics, sample effects, and binomial distribution approximation.

Two-Sample T-Test

Explains the two-sample t-test for comparing means of independent samples, including hypothesis testing steps and test statistic calculation.

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Understanding Statistics & Experimental Design

Covers basic probability theory, signal detection theory, statistics, and meta-statistics, explaining effect sizes, power, and hypothesis testing.

Normal Distribution: Characteristics and Examples

Covers the characteristics and importance of the normal distribution, including examples and treatment scenarios.

Statistical Inference: Confidence Intervals

Covers the construction of approximate confidence intervals using the central limit theorem for large sample sizes.

Optimality and Asymptotics

Explores the optimality of the Least Squares Estimator and its large sample distribution.

Hypothesis Testing & Confidence Intervals

Covers hypothesis testing, power, confidence intervals, and small sample considerations.

Multivariate Statistics: Wishart and Hotelling T²

Explores the Wishart distribution, properties of Wishart matrices, and the Hotelling T² distribution, including the two-sample Hotelling T² statistic.

Central Limit Theorem: Illustration and Applications

Explores the Central Limit Theorem and its statistical implications in random variables.