Repeated measures design

Formal sciences
Statistics
Statistical inference
Statistical hypothesis testing

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Related lectures (31)

Understanding Statistics & Experimental Design

Emphasizes the critical importance of understanding statistics to avoid errors in research and decision-making, using motivating examples and practical exercises.

ANOVA in Full Factorial Designs

Explores replicates, ANOVA, and factor elimination in full factorial designs using ANOM tables and model equations.

Variance and Covariance: Properties and Examples

Explores variance, covariance, and practical applications in statistics and probability.

Signal Detection Theory

Explores Signal Detection Theory and its impact on decision-making processes in statistics and experimental design.

Comparison Statistics: Hypothesis Testing and ANOVA

Explores comparison statistics, hypothesis testing, ANOVA, correlation, and linear regression.

Neural Signals and Signal Processing

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

ANOVA and Factorial Experiments

Explores ANOVA, factorial experiments, and model evaluation techniques.

GLM II

Explores GLM II, covering hypothesis testing, F-tests, multiple comparisons, and enriching the model to account for imaging artifacts.

Multicollinearity and Model Fit Analysis

Explores the dangers of 'big' models, multicollinearity issues, and model fit analysis in statistics for data science.

Analysis of Variance: ANOVA

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

Statistical Measures: Mean, Median, and Dispersion Techniques

Discusses statistical measures of central tendency and dispersion, focusing on mean, median, and their implications in data analysis.

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