Comprehensive study guide and lecture series on Statistics.
Learn the principles of Logistic Regression and the concept of the Odds Ratio, used when the outcome is categorical data like 'Pass/Fail' or 'Fraud/Normal' rather than a numerical value.
Understand the characteristics of time-ordered data where sequence matters, and learn the basics of forecasting using stationarity and ARIMA models.
Learn how prior beliefs (Prior) are updated with new information to become Posterior probabilities, exploring the core principles and practical applications of Bayes' Theorem.
Learn about non-parametric statistics, an analysis method for situations where normal distribution assumptions cannot be made, and the principles of Principal Component Analysis (PCA) for compressi...