Statistics and visualisation of morphometric data

Related lectures (32)

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

Explores model selection in statistics, discussing principles, probabilistic models, characteristics evaluation, and data visualization methods.

Explores probability theory, distribution of averages, and the central limit theorem.

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

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

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.

Introduces statistics basics, including data analysis and probability theory, emphasizing central tendency, dispersion, and distribution shapes.

Explains statistical methods in quantitative analysis, emphasizing precision, accuracy, and sample representation.

Covers the review of random variables, probability density functions, variance, and Gaussian processes.

Explores replicates, visualization methods, central tendency measures, outliers, dispersion, averages, residuals, and unbiased estimators.