Statistical Inference and Hypothesis Testing in Data Science

This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implic

• Define composite hypothesis and significance level
• Define test statistic and rejection region for hypothesis tests
• Perform tests on true population variance
• Compute sampling distributions for sample mean and minimum

• Basic statistical concepts
• Introductory data analysis knowledge