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Explores convergence in probability, concentration inequalities, laws of large numbers, and properties of distributions.
Explores variance estimation, creating personal estimators, correcting bias, and understanding Mean Square Error in statistical analysis.
Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.
Covers point estimation, confidence intervals, and hypothesis testing for smooth functions using mixed models and spline smoothing.
