Delves into the duality between confidence intervals and hypothesis tests, emphasizing the importance of precision and accuracy in estimation.
Introduces t-tests, focusing on hypothesis testing and comparing coefficients using the t-distribution.
Explores air pollution analysis using wind data, probability distributions, and trajectory models for air quality assessment.
Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Covers confidence intervals, hypothesis tests, standard errors, statistical models, likelihood, Bayesian inference, ROC curve, Pearson statistic, goodness of fit tests, and power of tests.
