Review Session: Module 1Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.
Interval EstimationCovers the construction of confidence intervals for a normal distribution with unknown mean and variance.
Testing: t-testsCovers t-tests, p-values calculation, and comparison of coefficients.
Probability and StatisticsCovers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.
Bayesian Parameter EstimationCovers an example of Bayesian parameter estimation and the trade-off between bias and variance in supervised learning.
Probabilities and StatisticsCovers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.
