# Working with Wikipedia

Wikipedia is a wonderful source of information for all of us while we are doing our time in this universe. Wiki is reliable as a rule and tries to do right when in doubt. For example, under Geostatistics Wiki points out, “This article is in need of attention from an expert on the subject. WikiProject Geography or the Geography Portal may be able to help recruit one”. No kidding! Wiki’s expert would have to be some kind of jack-of- all-sciences. So many disciplines do have a role to play in geography.

Geologists and mining engineers got stuck with geostatistics when Matheron goofed but thought he had dug up a new science. They were taught not work with the Central Limit Theorem and to infer ore between widely spaced boreholes. To infer ore between step-out boreholes at a spacing of 200-m worked well indeed in the Bre-X case. On the other hand, to infer spatial dependence between closely spaced pixels makes sense. When I tested for spatial dependence between gold grades of ordered rounds in a drift, Journel called me “too encumbered” with Fisher’s statistics. It’s not surprising then that geoscientists at Stanford are taught to assume, krige and smooth voodoo variances. Geoscientists with a passion for order tend to do curve-fitting. Too many are led to believe that geostatistics is good for geoscientists. I know that geoscientists would enjoy working with real statistics just as much as Sir Ronald A Fisher once did.

I tried to add applied statistics to Wiki’s Geostatistics when it was still called Kriging. I did so when I was a new Wikipedian in 2005. I knew then that geostatistics is an invalid variant of applied statistics. My son and I had known why since the early 1990s. What I didn’t know in 2005 is who stripped the variance off the distance-weighted average. But I do know now who did and when! What I do not know is why. I’ll continue to explain my case against geostatistics in concise terms and with significant symbols. I do so not only as a member of several ISO Technical Committees but also as a blogger, as a webmaster, and, last but not least, as a Wikipedian.

Most Wikipedians have a strong need to leave a better informed world than we found. I’m no exception. I hold an edge in always having worked with applied statistics and grasped Visman’s sampling theory and practice. I know that geostatistics converted Bre-X’s bogus grades and Busang’s barren rock into a massive phantom gold resource. What I also know is that bogus assays for three to five salted boreholes would have been enough to nip this mind-boggling fraud in the bud. The world’s mining industry doesn’t want to know is what I would have done!

Neither does Pierre-Jean Lafleur want to know. He is a Professional Engineer and a reserve and resource expert with Watts, Griffis, and McOuat Limited. He doesn’t believe I called the Bre-X fraud several months before the boss salter vanished. Lafleur wrote, “The information he provides is unclear, and most likely untrue”. So he wiped it off Wiki’s Bre-X Minerals. Neither may he believe it was not I who put my name on that Wiki subject. But what I did do when my name came up with the wrong context was add the facts and a few links to subjects such as spatial dependence and sampling variogram.

Lafleur deserves some praise because he doesn’t work under a nom-de-plume. Too many Wikipedians work anonymously. When scientists and engineers want to be taken seriously on Wikipedia they should stand up and be counted. Wikipedia should not allow Wikipedians who hide behind pseudonyms to delete indisputable scientific facts. Examples in my discipline of sampling and statistics are the Central Limit Theorem, functional dependence, spatial dependence and degrees of freedom.

Look and see which stats derive from Matheron’s Formule des Minerais Connexes. What a pity that the seminal work of the Creator of Geostatistics and the Founder of Spatial Statistics is no longer posted on the web. In fact, Matheron was a self-made wizard of odd statistics. Here’s a link to Matheron’s correction of his very first paper. All I did was use Matheron’s corrected lead and silver grades and the variances of those grades. Enter a different number of core samples and see how the Central Limit Theorem impacts 95% confidence limits. Play with real statistics and find out what geostatisticians are missing.

Professional engineers and geoscientists claim to be guided by codes of ethics that protect the public at large. Provincial securities commissions in Canada employ reserve and resource experts to set the rules. But should foxes run henhouses? That’s a good-enough reason why a National Securities and Exchange Commission should turn provincial fiefdoms into branch offices. Reserve and resource experts in branch offices should then be asked to testify under oath and explain why the Central Limit Theorem and degrees of freedom are null and void in geostatistics.

Working with applied statistics is fun. And it’s kind of cool for our planet! Wikipedians should read what the International Association for Standardization is all about. ISO may violate the odd copyright, and ignores priority once in a while. And the UN is not perfect either. Only Wikipedia can bring scientific integrity to the world.