The Design of Experiments: Difference between revisions
imported>Gareth Leng No edit summary |
imported>Gareth Leng No edit summary |
||
Line 1: | Line 1: | ||
{{subpages}} | {{subpages}} | ||
{|align="right" cellpadding="10" style="background-color:#FFFFCC; width:50%; border: 1px solid #aaa; margin:20px; font-size: | {|align="right" cellpadding="10" style="background-color:#FFFFCC; width:50%; border: 1px solid #aaa; margin:20px; font-size: 90%;" | ||
| | | | ||
"WHEN any scientific conclusion is supposed to be proved on experimental evidence, critics who still refuse to accept the conclusion are accustomed to take one of two lines of attack. They may claim that the interpretation of the experiment is faulty, that the results reported are not in fact those which should have been expected had the conclusion drawn been justified, or that they might equally well have arisen had the conclusion drawn been false. Such criticisms of interpretation are usually treated as falling within the domain of statistics. They are often made by professed statisticians against the work of others whom they regard as ignorant of or incompetent in statistical technique and, since the interpretation of any considerable body of data is likely to involve computations, it is natural enough that questions involving the logical implications of the results of the arithmetical processes employed, should be relegated to the statistician. At least I make no complaint of this convention. The statistician cannot evade the responsibility for understanding the processes he applies or recommends. My immediate point is that the questions involved can be dissociated from all that is strictly technical in the statistician's craft, and, when so detached, are questions only of the right use of human reasoning powers, with which all intelligent people, who hope to be intelligible, are equally concerned, and on which the statistician, as such, speaks with no special authority. The statistician cannot excuse himself from the duty of getting his head clear on the principles of scientific inference, but equally no other thinking man can avoid a like obligation. | "WHEN any scientific conclusion is supposed to be proved on experimental evidence, critics who still refuse to accept the conclusion are accustomed to take one of two lines of attack. They may claim that the interpretation of the experiment is faulty, that the results reported are not in fact those which should have been expected had the conclusion drawn been justified, or that they might equally well have arisen had the conclusion drawn been false. Such criticisms of interpretation are usually treated as falling within the domain of statistics. They are often made by professed statisticians against the work of others whom they regard as ignorant of or incompetent in statistical technique and, since the interpretation of any considerable body of data is likely to involve computations, it is natural enough that questions involving the logical implications of the results of the arithmetical processes employed, should be relegated to the statistician. At least I make no complaint of this convention. The statistician cannot evade the responsibility for understanding the processes he applies or recommends. My immediate point is that the questions involved can be dissociated from all that is strictly technical in the statistician's craft, and, when so detached, are questions only of the right use of human reasoning powers, with which all intelligent people, who hope to be intelligible, are equally concerned, and on which the statistician, as such, speaks with no special authority. The statistician cannot excuse himself from the duty of getting his head clear on the principles of scientific inference, but equally no other thinking man can avoid a like obligation. |
Revision as of 05:45, 11 February 2009
"WHEN any scientific conclusion is supposed to be proved on experimental evidence, critics who still refuse to accept the conclusion are accustomed to take one of two lines of attack. They may claim that the interpretation of the experiment is faulty, that the results reported are not in fact those which should have been expected had the conclusion drawn been justified, or that they might equally well have arisen had the conclusion drawn been false. Such criticisms of interpretation are usually treated as falling within the domain of statistics. They are often made by professed statisticians against the work of others whom they regard as ignorant of or incompetent in statistical technique and, since the interpretation of any considerable body of data is likely to involve computations, it is natural enough that questions involving the logical implications of the results of the arithmetical processes employed, should be relegated to the statistician. At least I make no complaint of this convention. The statistician cannot evade the responsibility for understanding the processes he applies or recommends. My immediate point is that the questions involved can be dissociated from all that is strictly technical in the statistician's craft, and, when so detached, are questions only of the right use of human reasoning powers, with which all intelligent people, who hope to be intelligible, are equally concerned, and on which the statistician, as such, speaks with no special authority. The statistician cannot excuse himself from the duty of getting his head clear on the principles of scientific inference, but equally no other thinking man can avoid a like obligation.
|
The Design of Experiments was writtten by R.A. Fisher(1890-1962) in 1935, aimed at "illustrating the principles of successful experiments".[1] Fisher was one of the leading scientists of the 20th century, and made major contributions to Statistics, Evolutionary Biology and Genetics. According to Anders Hald writing in A History of Mathematical Statistics (1998), "Fisher was a genius who almost single-handedly created the foundations for modern statistical science."[2]
Fisher made statistics an integral part of the Scientific method[3]
"To call in the statistician after the experiment is done may be no more than asking him to perform a postmortem examination: he may be able to say what the experiment died of." R.A. Fisher, at Indian Statistical Congress, Sankhya, ca 1938.
The Design of Experiments and his earlier Statistical Methods for Research Workers (1925) established formal methods for rigorously evaluating the outcomes of controlled experiments.
Fisher was also a writer of great elegance and wit: the extract on the right is about 'The Grounds on which Evidence is Disputed' from The Design of Experiments.
References
- ↑ Fisher RA (1935) The Design of Experiments Oliver and Boyd, Edinburgh
- ↑ A Guide to R. A. Fisher
- ↑ RA Fisher Obituary in The Times