Analysis of variance

Formal sciences
Statistics
Statistical inference
Statistical hypothesis testing

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Principal Components: Properties & Applications

Explores principal components, covariance, correlation, choice, and applications in data analysis.

Understanding Statistics & Experimental Design

Covers basic probability theory, ANOVA, experimental design, and statistical reporting errors.

Understanding Statistics & Experimental Design

Provides an overview of basic probability theory, ANOVA, t-tests, central limit theorem, metrics, confidence intervals, and non-parametric tests.

Analysis of Variance: ANOVA

Covers Analysis of Variance (ANOVA) to compare means of multiple groups efficiently.

Statistical Tests: T-Tests and ANOVA

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

Statistical Mediation and Moderation

Explores statistical mediation, moderation, ANOVA, and hypothesis testing.

Modeling Elasticity and Coefficients

Explores correlation matrices, regression, variance, confidence intervals, and standardized systems in statistical modeling.

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.

Neural Signals and Signal Processing

Delves into neural signals, GLM, ANOVA, brain mapping, connectivity, and multivariate methods.

Understanding Statistics & Experimental Design

Explores t-tests, confidence intervals, ANOVA, and hypothesis testing in statistics, emphasizing the importance of avoiding false discoveries and understanding the logic behind statistical tests.