Develop the basic methodology of hypothesis testing for statistical analysis of experimental and simulation studies. Through lectures and exercises using Python, explore the fundamentals of probability theory, population statistics, and statistical methods including p-values, t-test, U-test, Welch test, confidence intervals, single and multivariate analyses, and correlations. Extend these concepts with discussion of information theory, mutual information, and experimental design.
Students who have not learned the basics of statistical methods and will conduct experimental studies or numerical simulations in the future are encouraged to take the course.
Students are expected to have basic knowledge of elementary mathematics such as differentiation, integration, and elementary linear algebra. However, whenever necessary, mathematical details will be explained.
Students will need to write some code in Python.