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所在平台: Udemy |
课程主页: https://www.udemy.com/course/design-of-experiments/
课程评论：没有评论
**课程名称：** 实验设计 **课程概述：** 本课程深入探讨实验设计与分析（DoE）的基础知识。实验在科学、技术、产品设计与配方、商业化以及工艺改进等领域至关重要。清晰的实验设计是获取有效结果和结论的关键，因为这些结果和结论直接取决于数据的收集方式。 本课程旨在指导您如何**规划和实施实验**，以及**分析实验数据**，从而得出**有效且客观的结论**。 **课程内容亮点：** * **统计学基础：** 从基础统计概念入手，帮助您理解假设检验和方差分析（ANOVA）的原理。 * **因子设计（Factorial Designs）：** 学习因子及其交互作用的定义，理解如何设计包含多个实验因子的实验。 * **2 级因子设计：** 重点讲解常用的2级因子设计，包括全因子设计、区组设计和部分因子设计。 * **实际应用：** 课程中将穿插丰富的实际案例，帮助您更好地理解和掌握实验设计方法。 * **重点与分析：** 课程强调理解实验设计原则，并对实验结果进行批判性分析和讨论。 * **工具支持：** 数据分析将使用 Microsoft Excel 和 R-Studio。即使您不熟悉 R 语言，也能通过下载和简要解释的代码来学习和应用。 **谁适合学习？** 任何从事实验工作的人士都将从本课程中受益。 **课程学习目标：** 完成课程后，您将能够： * **选择最合适的实验设计** * **自信地分析实验数据** * **利用图表、等高线图和表格等方式呈现和讨论实验结果**
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.
