Design of Experiments DOE

所在平台: Udemy

课程主页: https://www.udemy.com/course/design-of-experiments-experimental-design-doe/

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课程简介

课程名称:实验设计(Design of Experiments, DOE) 课程概述: 实验设计(DOE)是一种统计工具,它帮助您正确设计任何实验,以便得出准确的结论。这个初学者在线课程通过实例教学,首先让您了解实验设计的概念及其目的,然后深入学习如何使用这一强大的工具来规划、执行和分析实验。课程中将介绍两种类型的因子设计:完全因子设计(Full Factorial Design)和分数因子设计(Fractional Factorial Design)。该教程旨在帮助初学者全面掌握实验的规划、执行和分析,从而得出正确的结论。对于科学家或工程师,尤其是在研发领域工作的人来说,这一工具是必不可少的,同时对于从事六西格玛实践的人也是至关重要的。 课程结构: 第一部分:让学生熟悉实验设计的定义、噪声因素、关系和水平。 第二部分:教授如何设置相关参数,以便使用完全或分数因子设计规划实验。 第三部分:学习如何执行实验,以确保结果的最高准确性。 第四部分:使用两种不同的方法分析实验获得的结果,包括图表表示法和方差分析(双因素ANOVA)。 通过该课程,您将获得必要的知识和技能,以进行有效的实验设计,从而推动科研和工程项目的发展。

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课程详情

Design of Experiments ( DOE ) is a statistical tool which helps you to design any experiment properly toward right conclusions. In this beginner online course, you learn by examples and you will know first what is design of experiment and the aim behind it, then you will go deeper thus learning how to plan, execute and analyze any experiment properly using this powerful tool. You will also encounter both types of factorial designs here ( Full Factorial Design and Fractional Factorial Design). This tutorial will allow any newbie fully learn how to plan, execute and analyze any experiment properly, thus making the right conclusions out it. This tool is obligatory for any scientist or engineer, especially those working within the research and development sector and is also essential for those who practice and work with six sigma.The course starts preparing you in PART I, thus making you familiar with the DOE definition, noise factors, relations and levels.Part II then teaches you how to set all the relevant parameters so that you can then plan your experiment using the full or fractional factorial designs.In Part III, you will learn how to execute your experiment afterwards in a way that you ensure highest accuracy in the results.In part IV, you will then learn how to analyze the acquired results in your experiments using two different ways, either by charts, or by analysis of variance (Two-way ANOVA).

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