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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/factorial-fractional-factorial-designs
课程评论：没有评论
课程名称：因子和分式因子设计 课程概述： 在工程、科学和商业领域，许多实验涉及多个因素。本课程介绍了多因子实验的基本知识，重点在于因子设计，即一种同时变更多个因素的实验策略。课程内容包括如何设计这些实验，并利用方差分析（ANOVA）来分析所得数据。实验中常常会涉及干扰因素，而通过区组原则可以在因子设计中处理这些情况。随着关注因素数量的增加，完整因子实验变得过于昂贵，因此分式因子设计成为一种有用的替代方案。本课程将涵盖分式因子的优点，以及构建和分析这些实验数据的方法。 课程大纲： - 单元 1：因子设计简介 - 单元 2：2^k 因子设计 - 单元 3：2^k 因子设计中的区组与混淆 - 单元 4：两级分式因子设计
Name:Unit 1: Introduction to Factorial Design
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Name:Unit 2: The 2^k Factorial Design
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Name:Unit 3: Blocking and Confounding in the 2^k Factorial Design
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Name:Unit 4: Two-Level Fractional Factorial Designs
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Many experiments in engineering, science and business involve several factors. This course is an introduction to these types of multifactor experiments. The appropriate experimental strategy for these situations is based on the factorial design, a type of experiment where factors are varied together. This course focuses on designing these types of experiments and on using the ANOVA for analyzing the resulting data. These types of experiments often include nuisance factors, and the blocking principle can be used in factorial designs to handle these situations. As the number of factors of interest grows full factorials become too expensive and fractional versions of the factorial design are useful. This course will cover the benefits of fractional factorials, along with methods for constructing and analyzing the data from these experiments.
