Testing hypotheses suggested by the data

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Related lectures (32)

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Covers point estimation, confidence intervals, and hypothesis testing for smooth functions using mixed models and spline smoothing.

Statistical Analysis: Hypothesis Testing and Distribution Models

Covers statistical analysis techniques, hypothesis testing, and distribution models using R software.

Comparison Statistics: Hypothesis Testing and ANOVA

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

Linear Independence: Covariance and Statistical Dependence

Explores covariance, statistical dependence, education-fertility relationship, hypothesis testing, and comparison statistics for continuous outcomes.

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.

Multiple Hypothesis Testing

Explores the challenges of multiple hypothesis testing and non-parametric estimation techniques.

Understanding Statistics & Experimental Design

Explores unequal variances, replication, power, effect size, biases, and their impact on research outcomes.

GLM II

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

Linear Regression Analysis: Diagnostic and Variance

Explores linear regression diagnostic methods, variance analysis, and experimental design concepts.

Neural Signals and Signal Processing

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