[SciPy-User] [SciPy-user] Anova and the level of significance
Sat Apr 10 12:29:11 CDT 2010
On Sat, Apr 10, 2010 at 12:42 PM, guts <firstname.lastname@example.org> wrote:
> I used the #f_oneway method from scipy.stats to compute the f_value and the
> critical value. To test it, i used the groups given in this book , which
> Measurements 1 2 3
> 1 0.0972 0.1382
> 2 0.0971 0.1432
> 3 0.0969 0.1382
> 4 0.1954 0.1730
> 5 0.0974 0.1383
> The F-value calculated is: 66.4 and the critical value is
> 3:89 (with a level of significance of 0.05).
> Those returned by the f_oneway method are, respectively: 66.37 and
> I don't understand why the critical value is so much smaller. I wanted to
> get the level significance from the method
> but didn't find how. Do you have an explanation for this number?
It took me a bit of time to figure out the degrees of freedom for your example
3.89 is the f-value at a significance level of 0.05
>>> stats.f.sf(3.89, 2, 15-3)
For this dataset, the f-value is much higher than the 5% critical
value, this means that the p-value, i.e. the probability that the f
value of 66.37 would be observed under the null hypothesis is tiny
>>> stats.f.sf(66.37, 2, 15-3)
So the null hypothesis of identical means (no differences across
groups) can be rejected with a very high confidence level.
array([ 0.1168 , 0.14618, 0.60782])
I hope this helps,
(I have verified f_oneway against the NIST benchmark cases, and the
results are correct except for very badly scaled examples.)
> Thanks for the help!
> : Measuring computer performance: a practitioner's guide, By David J.
> Stephane Campinas
> View this message in context: http://old.nabble.com/Anova-and-the-level-of-significance-tp28194677p28194677.html
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