ANOVA and experimental design

This second course in statistical modeling will introduce students to the study of analysis of variance (ANOVA), analysis of covariance (ANCOVA), and experimental design. ANOVA and ANCOVA, presented as a type of linear regression model, will provide the mathematical foundation for designing experiments for data science applications. Particular attention will be paid to important design concepts such as randomization, blocking, factorial design, and causal inference. Some attention will also be paid to ethical issues that arise when conducting experiments. This course can be taken for credit toward CU Boulder's Master of Science in Data Science (MS-DS) program, offered on Coursera. The MS-DS is an interdisciplinary degree that includes faculty from CU Boulder's Applied Mathematics, Computer Science, Information Science, and other departments. The MS-DS is a learning outcomes-based, no-application program that is ideal for individuals with a broad educational background and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Logo adapted from a photo by Vincent Ledvina on Unsplash