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Design and Analysis of Experiments
第3次开课
开课时间: 2021年07月07日 ~ 2021年09月29日
学时安排: 4小时每周
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spContent=As the core course of statistics major, this course aims to enable students to: 1) develop a statistical thought with application and logicality; 2) apply statistical methods to real-world problems through a quantity of examples; 3) learn how to process data by using R software.
As the core course of statistics major, this course aims to enable students to: 1) develop a statistical thought with application and logicality; 2) apply statistical methods to real-world problems through a quantity of examples; 3) learn how to process data by using R software.
—— 课程团队
课程概述

Statistics is one of the advantaged-discipline of East China Normal University. During the 4th China University Subject Rankings (CUSR), the statistics discipline of ECNU was sorted into grade A, and has now entered the ranks of key built disciplines of Shanghai and national first-class discipline.

This course, at the same time, can be used as a powerful tool for data collection and analysis. It has been widely applied in experimental science, product design, management science and social science.

This course covers detailed explanation of mathematical models and implementation of R software. In addition to single-factor experiment, multi-factor experiment, block design, Latin square design, factorial experiment, this course also provides students with videos introducing R software, R code and its description with high readability, sample data and other resources. Building on these foundations it enables students to analyze data in a practical way.

The textbook of this course is Design and Analysis of Experiments (English version) (8th ed). The book is based on college-level courses in design of experiments that Professor Montgomery has taught over nearly 40 years at Arizona State University, the University of Washington, and the Georgia Institute of Technology. It has been selected as a professional textbook of statistics by many famous universities both at home and abroad. The content includes simple comparative experiments, block design, factorial designs, response surface methods and designs, robust parameter design, etc.


课程大纲
Introduction
1.1 Strategy of Experimentation
1.2 Some typical applications
1.3 Basic principals
1.4 A brief history of experimental design
Simple comparative experiments
2.1 Basic concepts of Statistics
2.2 Sampling and sampling distributions
2.3 Graphic method
2.4 Statistical inference of mean value of two independent samples
2.5 Statistical inference of mean value of paired samples
2.6 Statistical inference of variances of normal distributions
Single factor experiment
3.1 Exploratory analysis
3.2 Analysis of variance
3.3 Analysis of fixed effect model
3.4 Model diagnosis
3.5 Comparisons among treatment means
3.6 Dispersion effect analysis
3.7 Analysis of random effect model
Randomized block and Latin square
4.1 Complete randomized block design
4.2 Latin square design
4.3 Orthogonal Latin square design
Introduction to factorial designs
5.1 Basic concepts of factorial design
5.2 Advantages of factorial design
5.3 The two-factor factorial design
5.4 The general factorial design
5.5 Fitting response curves and surfaces
5.6 Blocking in a factorial design
2 ^ k factorial design
6.1 2 ^ 2 factorial design
6.2 2 ^ 3 factorial design
6.3 The general 2 ^ k factorial design
6.4 Single repetition of 2 ^ k factorial design
6.5 Design of adding center points
展开全部
预备知识

Prerequisite couses: probability and mathematical statistics

参考资料

Textbook:

Design and analysis of experiments (8th edition), Douglas C. Montgomery, Wiley, 2013, ISBN: 978-1-118-14692-7.


East China Normal University
1 位授课老师
Yingchun ZHOU

Yingchun ZHOU

Professor

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