How to Lie with Statistics

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Related lectures (31)

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Variance, Covariance, and Correlation

Explores variance, covariance, and correlation in statistics, essential for data analysis.

Tonality: Pitch Profiles Analysis

Explores tonality, pitch profiles, key distance, and statistical analysis of pitch classes, using pitch spaces to analyze pitch distributions and the Tonnetz for a different tonality.

Dependence Concepts and Copulas

Explores dependence concepts, copulas, correlation fallacies, and rank correlations in statistics.

Red bus/Blue bus paradox

Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.

Real Estate Data Analysis: Descriptive Statistics

Explores real estate data analysis through descriptive statistics, correlation, regression, and forecasting methods.

Introduction to Data Analysis

Introduces data analysis basics, statistical concepts, Python libraries, and real-world applications.

Causality and Invariant Machine Learning

Explores causality, correlation, and spurious correlations in machine learning, emphasizing bias mitigation and invariance across environments.

Quantifying Statistical Dependence: Covariance and Correlation

Explores covariance, correlation, and mutual information in quantifying statistical dependence between random variables.

Probability and Statistics

Covers probability, statistics, independence, covariance, correlation, and random variables.

Complex Systems: Epidemics

Delves into complex systems, strange attractors, and epidemics, emphasizing the influence of psychological factors and the role of contagion.