Statistics and visualisation of morphometric data

Related lectures (32)

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Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Introduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.

Introduces probability theory, random variables, and distributions, with a focus on their applications in atomic diffusion.

Covers broadcasting, operations, comparisons, and numpy constants like pi, e, and infinity.

Explores air pollution analysis using wind data, probability distributions, and trajectory models for air quality assessment.

Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.

Covers amplitude shift keying and various data analysis techniques using Jupyter Notebooks.

Covers the characteristics and importance of the normal distribution, including examples and treatment scenarios.