Introduction to Statistical Methodology

4.0 credits

This course is an introduction to statistical methodology that focuses on the mathematical and computational tools needed to practically apply such methods. Topics to be covered include data exploration and summarization, elementary probability, combinatorics, random variables, distribution theory, parameter estimation, and methods of statistical inference, including hypothesis tests and confidence intervals for one and two sample means and proportions, ANOVA, contingency table analyses, and regression analysis, including multiple regression. Students will perform calculations with the statistical software R/RStudio. This course is recommended for students majoring in Statistics, Economics, Computer Science, Data Science, or Business or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. Students may earn degree credit for only one of these courses: STAT 180, STAT 190, STAT 212, STAT 213, ECON 230, PSCI 200.