Colin

You need to bear in mind that statistical tests such

as t and F are only testing a very simple hypothesis -

they do not test whether the samples are from the same

population.

The F test is to check whether the standard deviations

differ. If the ore is from the same genesis, it is

likely that the variability will be constant and your

F test will not be significant.

The t test is against the hypothesis that the average

values are the same. That is, one population has a

higher average grade than the other. You can have the

same variability around the mean, but have a zone

where the minerals tend to concentrate at a higher

average.

Even if both tests are not significant, this does not

'prove' that the two populations are the same. You

could have two sets of data with the same mean and

standard deviation and completely different shapes,

for example.

To include the spatial element, you could try a cross

validation approach where one set of samples is the

'actual' values and you try to estimate those from the

other set. This will show up consistent differences in

average between the two as well as differences in

variability.

Strictly, all of the above requires a Normal

distribution but with your not-too-skewed data and

thousands of samples, the Central Limit Theorem should

take care of those problems.

Isobel

http://uk.geocities.com/drisobelclark