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Lecture
Network Averaging: Theory and Applications
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Statistical Analysis of Network Data: Structures and Models
Explores statistical analysis of network data, covering graph structures, models, statistics, and sampling methods.
Covariances and Random Variable Sums: Insights and Applications
Covers advancements in sensory feedback restoration through peripheral nerve stimulation and the integration of cognitive complexity in prosthetic technology.
Introduction to Comparison Statistics
Introduces comparison statistics, error rates, hypothesis testing, and real-life examples of treatment effectiveness and weightlifting analysis.
Review Session: Module 1
Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.
Sampling Theory: Statistics for Mathematicians
Covers the theory of sampling, focusing on statistics for mathematicians.
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.
Hypothesis Testing: Q-Q Plots and Non-Parametric Tests
Covers hypothesis testing, Q-Q plots, and non-parametric tests in statistics.
Two-Sample T-Test
Explains the two-sample t-test for comparing means of independent samples, including hypothesis testing steps and test statistic calculation.
Understanding Statistics & Experimental Design
Explores unequal variances, replication, power, effect size, biases, and their impact on research outcomes.
Statistical analysis of network data
Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.
