Goodreads helps you keep track of books you want to read.
Start by marking “The Design of Experiments” as Want to Read:
Blank 133x176
The Design of Experiments
Ronald A. Fisher
Rate this book
Clear rating
Open Preview

The Design of Experiments

4.2  ·  Rating Details ·  5 Ratings  ·  2 Reviews

1. Introduction
2. The principles of experimentation, illustrated by a psycho-physical experiment
3. A historical experiment on growth rate
4. An agricultural experiment in randomised blocks
5. The latin square
6. The factorial design in experimentation
7. Confounding
8. Special cases of partial confounding
9. The increase of precision by concomitant measurements. Statisti
8th, 245 pages
Published 1960 by Oliver and Boyd
More Details... edit details

Friend Reviews

To see what your friends thought of this book, please sign up.

Reader Q&A

To ask other readers questions about The Design of Experiments, please sign up.

Be the first to ask a question about The Design of Experiments

This book is not yet featured on Listopia. Add this book to your favorite list »

Community Reviews

(showing 1-35)
filter  |  sort: default (?)  |  Rating Details
Mar 27, 2014 Chrissy rated it liked it
It's difficult to treat this statistical hallmark fairly from a modern perspective, and particularly from the perspective of a social scientist. Fisher's work, while undeniably fundamental to current statistical techniques in psychology, lay firmly in the applied realms of genetics and agriculture. Whereas it is possible to read his treatment of Latin Squares in plots of land, for example, as generalizable to the design of factorial behavioural experiments, holy hell is it tedious: it demands ...more
Jul 25, 2010 loafingcactus rated it really liked it
Charmingly written in the old gentleman's style, which is of especial note since this book marks the delineation between the physician as a gentleman relying on his superior intuition and sense and the physician as a technitian creating inputs and enacting outputs from scientific method.
Sharan Banagiri
Sharan Banagiri rated it it was amazing
Jun 10, 2016
Juan Ortega
Juan Ortega rated it it was amazing
Jan 09, 2015
Marina rated it really liked it
Feb 22, 2013
Mike marked it as to-read
Mar 06, 2013
Ran marked it as to-read
Jun 04, 2013
Kim Klima
Kim Klima marked it as to-read
Jun 15, 2013
Jerzy marked it as to-read
Aug 17, 2013
Mary Baldwin
Mary Baldwin marked it as to-read
Sep 06, 2013
Alberto Celio
Alberto Celio marked it as to-read
Oct 23, 2013
Elisa marked it as to-read
Nov 04, 2013
Akshay Chalana
Akshay Chalana marked it as to-read
Nov 19, 2013
Nandita Maan
Nandita Maan marked it as to-read
Jan 12, 2014
Daniel marked it as to-read
Feb 13, 2014
Mikkel Jørgensen
Mikkel Jørgensen marked it as to-read
Apr 25, 2014
Suneet Jindal
Suneet Jindal marked it as to-read
May 09, 2014
Ema marked it as to-read
May 14, 2014
Martin marked it as to-read
May 15, 2014
Piotr marked it as to-read
Jul 09, 2014
Rajkamal Rabha
Rajkamal Rabha marked it as to-read
Jul 26, 2014
Abigail Advincula
Abigail Advincula marked it as to-read
Jul 28, 2014
Yogesh Singla
Yogesh Singla marked it as to-read
Aug 17, 2014
Ngangom Shakti
Ngangom Shakti marked it as to-read
Aug 24, 2014
Alexia Gaudeul
Alexia Gaudeul marked it as to-read
Aug 25, 2014
Vijay marked it as to-read
Oct 07, 2014
Sweta Singh
Sweta Singh marked it as to-read
Oct 25, 2014
Shivshankar marked it as to-read
Dec 02, 2014
皓宇 莊
皓宇 莊 marked it as to-read
Feb 26, 2015
Jonas marked it as to-read
Mar 20, 2015
Aisling marked it as to-read
May 24, 2015
Chris Lee
Chris Lee marked it as to-read
May 31, 2015
Bryguy marked it as to-read
Aug 01, 2015
Sivan Mauer
Sivan Mauer is currently reading it
Nov 02, 2015
There are no discussion topics on this book yet. Be the first to start one »
Sir Ronald Aylmer Fisher was an English statistician, evolutionary biologist, geneticist, and eugenicist.

Among other things, Fisher is well known for his contributions to statistics by creating ANOVA (analysis of variance), Fisher's exact test and Fisher's equation.
More about Ronald A. Fisher...

Share This Book

“The value for which P=0.05, or 1 in 20, is 1.96 or nearly 2; it is convenient to take this point as a limit in judging whether a deviation ought to be considered significant or not. Deviations exceeding twice the standard deviation are thus formally regarded as significant. Using this criterion we should be led to follow up a false indication only once in 22 trials, even if the statistics were the only guide available. Small effects will still escape notice if the data are insufficiently numerous to bring them out, but no lowering of the standard of significance would meet this difficulty.” 1 likes
More quotes…