A First Course in Design and Analysis of Experiments

Covers the basic topics in experimental design and analysis and is intended for graduate students and advanced undergraduates.

**Tag(s):**
Statistics

**Publication date**: 01 Jan 2010

**ISBN-10**:
0716735105

**ISBN-13**:
9780716735106

**Paperback**:
679 pages

**Views**: 10,430

**Type**: N/A

**Publisher**:
W. H. Freeman and Company

**License**:
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported

**Post time**: 26 Jun 2016 12:00:00

A First Course in Design and Analysis of Experiments

Covers the basic topics in experimental design and analysis and is intended for graduate students and advanced undergraduates.

You are free to:

Share — copy and redistribute the material in any medium or format

The licensor cannot revoke these freedoms as long as you follow the license terms.

Click**here** to read the full license.

Share — copy and redistribute the material in any medium or format

The licensor cannot revoke these freedoms as long as you follow the license terms.

Click

From the Preface:

Gary W. Oehlert wrote:This text covers the basic topics in experimental design and analysis and is intended for graduate students and advanced undergraduates. Students should have had an introductory statistical methods course at about the level of Moore and McCabe’s Introduction to the Practice of Statistics (Moore and McCabe 1999) and be familiar with t-tests, p-values, confidence intervals, and the basics of regression and ANOVA. Most of the text soft-pedals theory and mathematics, but Chapter 19 on response surfaces is a little tougher sledding (eigenvectors and eigenvalues creep in through canonical analysis), and Appendix A is an introduction to the theory of linear models. I use the text in a service course for non-statisticians and in a course for first-year Masters students in statistics. The non-statisticians come from departments scattered all around the university including agronomy, ecology, educational psychology, engineering, food science, pharmacy, sociology, and wildlife.

Tweet

About The Author(s)

Gary W. Oehlert, Ph.D. is a statistical consultant for Stat-Ease, Inc. He has a long list of achievements in the field of statistics, and in particular, design of experiments (DOE). Gary teaches courses in DOE in the School of Statistics at the University of Minnesota, where he is a professor of applied statistics. He has also taught at Princeton University and the University of California, Berkeley.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Rexx
Microsoft .NET
Perl
PHP
R
Python
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors