Many experiments involve factors whose levels are chosen at random. A well-know situation is the study of measurement systems to determine their capability. This course presents the design and analysis of these types of experiments, including modern methods for estimating the components of variability in these systems. The course also covers experiments with nested factors, and experiments with hard-to-change factors that require split-plot designs. We also provide an overview of designs for experiments with response distributions from nonnormal response distributions and experiments with covariates.
This course is part of the Design of Experiments Specialization
About this Course
What you will learn
Design and analyze experiments where some of the factors are random
Design and analyze experiments where there are nested factors or hard-to-change factors
Analyze experiments with covariates
Design and analyze experiments with nonnormal response distributions
Syllabus - What you will learn from this course
Unit 1: Experiments with Random Factors
Unit 2: Nested and Split-Plot Designs
Unit 3: Other Design and Analysis Topics
- 5 stars75.86%
- 4 stars10.34%
- 3 stars13.79%
TOP REVIEWS FROM RANDOM MODELS, NESTED AND SPLIT-PLOT DESIGNS
Very exhaustive information about random models and nested and split-plot designs. Thank you to Professor Douglas C. Montgomery and Coursera Team.
Comprehensive and practical course in the Design of Experiments specialization. Helps reinforce the need for a physical experiment to align with constraints on randomization.
THIS FULL COURSE WAS EXCELLENT. IT WILL HELP IN MY PROJECT. THANK YO DOCTOR MONTGOMERY SIR.
About the Design of Experiments Specialization
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