Statistical Modeling: Estimation and Hypothesis Testing
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Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.
Covers confidence intervals, hypothesis tests, standard errors, statistical models, likelihood, Bayesian inference, ROC curve, Pearson statistic, goodness of fit tests, and power of tests.
Explores VaR estimation, confidence intervals, backtesting, multivariate distributions, and normality testing through QQ plots and the Jarque-Bera statistic.
