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 is part of the Statistical Modeling for Data Science Applications Specialization
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About this Course
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100% online
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Course 2 of 3 in the
Intermediate Level
Calculus, linear algebra, and probability theory.
Approx. 39 hours to complete
English
Skills you will gain
- Calculus
- and probability theory.
- Linear Algebra
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 3 in the
Intermediate Level
Calculus, linear algebra, and probability theory.
Approx. 39 hours to complete
English
Offered by
Start working towards your Master's degree
This course is part of the 100% online Master of Science in Data Science from University of Colorado Boulder. If you are admitted to the full program, your courses count towards your degree learning.
Syllabus - What you will learn from this course
11 hours to complete
Introduction to ANOVA and Experimental Design
11 hours to complete
9 videos (Total 87 min), 2 readings, 12 quizzes
9 hours to complete
Hypothesis Testing in the ANOVA Context
9 hours to complete
6 videos (Total 91 min), 2 readings, 6 quizzes
9 hours to complete
Two-Way ANOVA and Interactions
9 hours to complete
7 videos (Total 79 min)
10 hours to complete
Experimental Design: Basic Concepts and Designs
10 hours to complete
7 videos (Total 79 min), 2 readings, 7 quizzes
About the Statistical Modeling for Data Science Applications Specialization

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