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[SANET-MG] why is p=.o5 significant?
You are correct the m value is the mean of the proportion of male
births. The P value is related to the probability that a deviation from
the expected M=0.500 by chance , a a value p=0.05 is taken to be
statistically significant , while lower values are considered to be even
more significant. By normal convention the values reported such as .006
and .008 are agreed to be significant. The p value .05 was proposed to
be significant by the great population geneticist RA Fisher from
Oxford., who with Sewall Wright and JBS Haldane founded population
I am tempted to bore everyone with my meeting with RA Fisher in 1962 but
that does not add much to the question. I am enclosing below a fuller
discussion of of p 05 as a convention for significance of data and the
open sesame to the PhD exam :-)
he standard level of significance used to justify a claim of a
statistically significant effect is 0.05. For better or worse, the term
statistically significant has become synonymous with P0.05.
There are many theories and stories to account for the use of P=0.05 to
denote statistical significance. All of them trace the practice back to
the influence of R.A. Fisher. In 1914, Karl Pearson published his Tables
for Statisticians & Biometricians. For each distribution, Pearson gave
the value of P for a series of values of the random variable. When
Fisher published Statistical Methods for Research Workers (SMRW) in
1925, he included tables that gave the value of the random variable for
specially selected values of P. SMRW was a major influence through the
1950s. The same approach was taken for Fisher's Statistical Tables for
Biological, Agricultural, and Medical Research, published in 1938 with
Frank Yates. Even today, Fisher's tables are widely reproduced in
standard statistical texts.
Fisher's tables were compact. Where Pearson described a distribution in
detail, Fisher summarized it in a single line in one of his tables
making them more suitable for inclusion in standard reference works*.
However, Fisher's tables would change the way the information could be
used. While Pearson's tables provide probabilities for a wide range of
values of a statistic, Fisher's tables only bracket the probabilities
between coarse bounds.
The impact of Fisher's tables was profound. Through the 1960s, it was
standard practice in many fields to report summaries with one star
attached to indicate P 0.05 and two stars to indicate P 0.01,
Occasionally, three starts were used to indicate P 0.001.
Still, why should the value 0.05 be adopted as the universally accepted
value for statistical significance? Why has this approach to hypothesis
testing not been supplanted in the intervening three-quarters of a century?
It was Fisher who suggested giving 0.05 its special status. Page 44 of
the 13th edition of SMRW, describing the standard normal distribution,
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.
Similar remarks can be found in Fisher (1926, 504).
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