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.
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实验设计 专项课程亚利桑那州立大学课程信息
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第 4 门课程（共 4 门）
中级
完成时间大约为9 小时
英语（English）
字幕：法语（French）, （欧洲人讲的）葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
您将学到的内容有
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
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 4 门）
中级
完成时间大约为9 小时
英语（English）
字幕：法语（French）, （欧洲人讲的）葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
提供方
亚利桑那州立大学
Arizona State University has developed a new model for the American Research University, creating an institution that is committed to excellence, access and impact. ASU measures itself by those it includes, not by those it excludes. ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it.
授课大纲 - 您将从这门课程中学到什么
完成时间为 4 小时
Unit 1: Experiments with Random Factors
完成时间为 4 小时
6 个视频 （总计 44 分钟）, 5 个阅读材料, 3 个测验
完成时间为 2 小时
Unit 2: Nested and Split-Plot Designs
完成时间为 2 小时
6 个视频 （总计 64 分钟）, 1 个阅读材料, 2 个测验
完成时间为 3 小时
Unit 3: Other Design and Analysis Topics
完成时间为 3 小时
7 个视频 （总计 71 分钟）, 1 个阅读材料, 3 个测验
审阅
- 5 stars75%
- 4 stars10.71%
- 3 stars14.28%
来自RANDOM MODELS, NESTED AND SPLIT-PLOT DESIGNS的热门评论
由 ML 提供Nov 25, 2021
Comprehensive and practical course in the Design of Experiments specialization. Helps reinforce the need for a physical experiment to align with constraints on randomization.
由 RR 提供Jul 25, 2020
Very exhaustive information about random models and nested and split-plot designs. Thank you to Professor Douglas C. Montgomery and Coursera Team.
由 AA 提供Sep 25, 2020
THIS FULL COURSE WAS EXCELLENT. IT WILL HELP IN MY PROJECT. THANK YO DOCTOR MONTGOMERY SIR.
关于 实验设计 专项课程
Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others.
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