Statistical Tests

In this course, I will explain the basic methodology for hypothesis testing. Statistical analyses are required in many experimental and simulation studies. I will deliver lectures and exercises on the basics of probability theories and statistical methods including sample means, sample variances, p-values, t-test, u-test, Welch test, confidence intervals, covariance, ANOVA, multivariate analyses, correlations, information theory, mutual information, experimental design, and so on. After the course work, the students will acquire basic knowledge of hypothesis testing.

This course corresponds to the first half of the previous course "B07 Statistical Methods". 

Prerequisites or Prior Knowledge

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.