Covers broadcasting, operations, comparisons, and numpy constants like pi, e, and infinity.
Explores replicates, visualization methods, central tendency measures, outliers, dispersion, averages, residuals, and unbiased estimators.
Covers the review of random variables, probability density functions, variance, and Gaussian processes.
Covers the process of making pizza, sampling, averages, dispersion, residuals, and normal distribution.
Explores random variables, their variability, realization of random processes, and the scientific method in material science.
Explores the tradeoff between risk and return in portfolios, the benefits of diversification, and the impact of correlation on portfolio risk.
Introduces probability theory, random variables, and distributions, with a focus on their applications in atomic diffusion.
Explores statistical dispersion and its impact on determining normal values and data analysis.
Covers risk and return tradeoffs in portfolios, diversification benefits, and the efficient frontier with multiple assets.
Discusses bias and variance in statistical estimation, exploring the trade-off between accuracy and variability.
