David in November 1989 had rejected Merks and Merks Precision Estimates for Ore Reserves. He had done so because our paper was short on references to 20 years of geostatistical literature. In contrast, Erzmetall praised its “splendid preparation” and published it in October 1991. David didn’t know how to test for spatial dependence, how to count degrees of freedom, and how to derive unbiased confidence limits for gold grades and contents of in-situ ore. We did what David never got around to doing. We derived precision estimates for the mass of contained gold based on assays determined in a set of ordered rounds in a drift. The set of primary increments from each mined round had been put in the same basket. That’s why we couldn’t estimate the intrinsic variance of gold.

My son and I had taken at different times the same stats courses at Simon Fraser University. I had done so shortly after we came to Canada in October 1969. My problem in those days was that I spoke German and French better than English. I left SGS in 1980 to work with Cominco. I wrote a lot on sampling and statistics and lectured all over the world. These days I still write about sampling and statistics but my son travels a lot. Ed has a

This formula finds its origin in calculus and probability theory. It shows that the population variance of a general function is the sum of n variance terms, each of which is the squared partial derivative toward an independent variable multiplied by its variance. It has built a bridge

In 1970 Professor Dr Georges Matheron brought his new science of geostatistics to North America. In his Random Functions and their Application in Geology Matheron invoked Brownian motion along a straight line. It was just as richly embellished with symbols and as short on primary data as is his magnum opus. MarĂ©chal and Serra in Random Kriging applied the same symbols that Matheron had taught all of his disciples. Figure 10 puts in plain view how to do more with less.

David may have thought that what MarĂ©chal and Serra were doing was kind of cool. So, he explains it on page 286 of his 1977 textbook in Chapter 10 The Practice of Kriging. David dressed up M&S‘s Figure 10 with a slightly different caption.

David added a dash of subterfuge when he called his points within B “estimated”. Each point within B derives from the same set of measured values for nine (9) holes. As such, each and every one is a function of the same set of nine (9) holes. Of course, each distance-weighted average does have its own variance in applied statistics. Thus it came about that variance-deprived and zero-dimensional distance-weighted average point grades morphed into kriged estimates.

In Section 12.2.1 Using a simulated model of Chapter 12 Orebody Modelling (see page 324) David prevaricates, “The criticism to this model is obvious. The simulation is not reality. There is only one answer: The proof of the pudding is…! So far the few simulations made which it has been possible to check have a posteriori proved to be adequate”. Good grief! What about Bre-X? Why didn’t they ask Merks and Merks?

McGill University had set the stage in 1993 to praise Professor Dr Michel David. Those who had come to McGill’s Conference Center to praise him may still not have a clue what was wrong with geostatistics. But Bre-X's rigs were drilling at its Busang property! The Bre-X fraud came about because the geostatocracy had failed to grasp the properties of variances.