Prerequisites:Students are expected to have prior knowledge of basic linear algebra, including matrix operations and diagonalization, as well as foundational concepts in descriptive and inferential statistics, such as hypothesis testing. Familiarity with the R programming environment for basic data analysis tasks is also required.
DESCRIPTION
This course provides an introduction to statistical data analysis with a focus on managing, modeling, and analyzing datasets. Students will learn fundamental statistical techniques to work with large datasets and extract meaningful insights. Emphasis is placed on exploratory data analysis, statistical inference, regression, classification, and machine learning methods applied to real-world data.