Covers linear regression, correlation analysis, and logistic regression fundamentals, emphasizing the distinction between correlation and causation.
Covers probability, random variables, expectation, GLMs, hypothesis testing, and Bayesian statistics with practical examples.
Explores scientific misconduct, p-value optimization, and spotting issues with conclusions using real-world examples.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
