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2d
awarded  Constituent
Mar
20
comment The abundance of P values in absence of a hypothesis
That table is actually a good example of what happens with large sample sizes (even the small differences in average age appear to be significant, suggesting perhaps that average waistlines may widen with old age or perhaps that larger waists increase average life expectancy very slightly). But the $P$-values are not dominating the table and at best this is exploratory analysis which could provide hypotheses for future study (e.g. a longitudinal study seeing whether people's waists widen or whether they die). It also suggests some factors which might be worth controlling for in future work.
Mar
19
comment Why shouldn't the denominator of the covariance estimator be n-2 rather than n-1?
The denominator of your definition of sample variance is $n−1$ probably because this makes it an unbiased estimate of the population variance. The same is true of the sample covariance using the same denominator. But there are other definitions of sample statistics, with different denominators.
Mar
17
awarded  Caucus
Mar
10
revised want to apply zero in total for missing time in table a
format
Mar
9
awarded  Nice Answer
Mar
9
comment How multiple t-tests give rise to type I error
xkcd.com/882
Feb
26
answered Why is the standard deviation defined using differences^2 instead of differences^4?
Feb
21
awarded  Excavator
Feb
21
comment When does replication reveal fraud?
"Statistics means never having to say you're certain"
Feb
21
revised When does replication reveal fraud?
numbering disrupeted by whitespace
Jan
28
awarded  Yearling
Jan
25
comment How to tell the probability of failure if there were no failures?
If there are few or no failures then $\Theta \sim U(0,0.1)$ will produce almost the same result as $\Theta \sim U(0,1)$ i.e. Beta$(1,1)$, and the latter is easier to handle
Jan
12
comment Density estimation for streams of Data
You could store your data as counts in intervals, where the intervals are substantially narrower than the bandwith you are using for smoothing your kernel. Then you just need to remember as many numbers as there are intervals.
Jan
10
comment Measuring “almost the same” when significantly different
@Glen_b: I am looking for a summary measurement of "closeness" which is insensitive to scale (e.g. multiplying all the data by $10$) and can be used for meaningful comparisons with other splits of the same population by different factors and for comparisons with other cases for example when the success rates change.
Jan
10
comment Measuring “almost the same” when significantly different
There are other similar tables (such as gender, age, and ethnic origin) which show different disparities as well has having a variety of distributions between the size of the largest group and of the others. I was wondering if there was some sensible summary statistic that I had missed which like the $\chi^2$ statistic gave a greater weight to disparities in the larger groups but which was not so dependent on the total number of individuals as the $\chi^2$ statistic. For example the $\chi^2$ statistic divided by the total number of individuals would be unitless.
Jan
9
asked Measuring “almost the same” when significantly different
Jan
9
comment How to find $\displaystyle \dfrac{d}{dt} \left [\int_t^\infty xf(x)~dx \right ] $ (when $f(x)$ is a probability density function)
Use the fundamental theorem of calculus
Jan
9
comment How to find $\displaystyle \dfrac{d}{dt} \left [\int_t^\infty xf(x)~dx \right ] $ (when $f(x)$ is a probability density function)
Do you mean $\displaystyle \dfrac{d}{dt} \left [\int_t^\infty xf(x)~dx \right ]$? Perhaps $-tf(t).$ Or do you mean $\displaystyle \dfrac{d}{dt} \left [\dfrac{\int_t^\infty xf(x)~dx}{1-F(t)} \right ]$?
Jan
3
comment Explanation of formula for median closest point to origin of N samples from unit ball
I suspect it may be suggesting that in high dimensions, points to predict are effectively a long way from the training data, as if on the edge of a sphere, so you are not really interpolating but rather extrapolating, and so uncertainties are much greater. But I do not really know.