This course introduces the principles of statistical inference, including point and interval estimation, confidence intervals, and hypothesis testing. Students learn classical and Bayesian approaches, non-parametric tests, and criteria for comparing statistical methods. The course also covers linear regression and analysis of variance (ANOVA), focusing on model formulation, assumptions, and interpretation to solve real-world data problems.