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Learner Reviews & Feedback for ANOVA and Experimental Design by University of Colorado Boulder

4.0
stars
19 ratings

About the Course

This second course in statistical modeling will introduce students to the study of the 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 basis for designing experiments for data science applications. Emphasis will be placed on important design-related concepts, such as randomization, blocking, factorial design, and causality. Some attention will also be given to ethical issues raised in experimentation. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education 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 photo by Vincent Ledvina on Unsplash...

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1 - 7 of 7 Reviews for ANOVA and Experimental Design

By Rog

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Jun 11, 2024

The peer review assignments process is absolutely painful and ruins the experience.

By Birhane D A

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Feb 21, 2024

3

By Edgar O L C

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Jul 14, 2023

Great course for the research field, I think the topics discussed are important to know them to perform data science or if you are doing a research project at lab.

The experimental design could be imporved but they give a general presentation.

By Hidetake T

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Oct 29, 2022

High quality. Intensive course. I could gain insight enough for my work in data science.

By Zehu C

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Jul 31, 2022

Great course. Really useful and practical, and the exercise is not too difficult.

By Kodai F

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Aug 19, 2025

Easy to understand and very useful for practical work.

By matt t

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Apr 28, 2026

Presented terribly. Issues with materials and grading, and the peer review component is horrible.