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Updated in [May 25th, 2023]

What skills and knowledge will you acquire during this course?
By taking this course, students will acquire knowledge and skills related to the analysis of variance (ANOVA), analysis of covariance (ANCOVA), and experimental design. They will learn important design-related concepts such as randomization, blocking, factorial design, and causality. Additionally, they will gain an understanding of ethical issues raised in experimentation.

How does this course contribute to professional growth?
This course in ANOVA and Experimental Design provides students with the mathematical basis for designing experiments for data science applications. It covers important design-related concepts such as randomization, blocking, factorial design, and causality, as well as ethical issues raised in experimentation. By taking this course, students can gain the knowledge and skills necessary to design experiments for data science applications, which can contribute to their professional growth. Additionally, the MS-DS degree program offered on the Coursera platform provides students with an interdisciplinary education in computer science, information science, mathematics, and statistics, which can further enhance their professional growth.

Is this course suitable for preparing further education?
The course ANOVA and Experimental Design is suitable for preparing further education, as it provides students with the mathematical basis for designing experiments for data science applications. The course also covers important design-related concepts, such as randomization, blocking, factorial design, and causality, as well as ethical issues raised in experimentation. Furthermore, the course is part of the Master of Science in Data Science (MS-DS) degree offered on the Coursera platform, which 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.