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所在平台: Udemy |
课程主页: https://www.udemy.com/course/design-of-experiments-i/
课程评论：没有评论
**课程名称：** 实验设计与分析 (Design and Analysis of Experiments DoE) **课程概述：** 本课程是关于实验设计与分析 (DoE) 的基础知识。实验在科学、技术、产品设计与制造、商业化及工艺改进等领域扮演着重要角色。一个精心设计的实验至关重要，因为实验结果和结论的有效性取决于数据收集的方式。 本课程旨在教授如何规划与执行实验，以及如何分析实验数据以获得有效和客观的结论。课程将从基础统计概念入手，介绍假设检验和方差分析的原理。随后，将引入因子设计，包括因子效应和交互作用的定义。课程重点关注常用的两水平因子设计，涵盖全因子设计、区组设计和部分因子设计。课程中将通过大量实际案例来帮助理解。 课程侧重于理解实验设计的基本原理，以及对实验结果进行批判性分析和讨论。数据分析将使用 MS Excel 和 R-Studio。尽管这不是一门 R 语言课程，但即使是 R 语言初学者也能从课程中受益。课程提供的 R 代码可供下载，函数解释将简明扼要，代码也易于修改以适应学生自己的数据分析。 任何进行实验的人都将从本课程中获益。 **课程目标：** 完成本课程后，学生将能够： * 选择最合适的实验设计。 * 自信地分析实验数据。 * 基于图表、等值线图和表格呈现和讨论结果。
This course covers the fundamentals of the design and analysis of experiments (DoE).Experimentation plays an important role in science, technology, product design and formulation, commercialization, and process improvement. A well-designed experiment is essential once the results and conclusions that can be drawn from the experiment depend on the way the data is collected.This course is about planning and conducting experiments and about analysing the resulting data in a way that valid and objective conclusions are obtained.The course begins with some basic statistics concepts to understand the fundamentals of hypothesis testing and analysis of variance. Then we introduce the idea of factorial designs, with the definition of effects and interactions between factors. The following sections will focus on the widely used 2-level factorial designs. We will cover full homogeneous designs, blocked designs, and fractional designs. The whole course is illustrated with practical examples to help with understanding.The course focuses on the understanding of the principles used in the design of experiments and on the critical analysis and discussion of the results.The analysis of the data will use MS Excel and R-Studio. Although this is not an R course, even students that are not familiar with R can enrol in it. The R codes used can be downloaded, the functions will be briefly explained, and the codes can be easily adapted to analyse the student's own data.Any person who performs experiments will benefit from this course.By the end of this course, the student will be able to:- Choose the most suitable experimental design;- Analyse the experimental data with confidence;- Present and discuss the results based on charts, contour plots, and tables.
