Dr Isobel Clark is the author of Practical Geostatistics. What she did in this 1979 textbook took me by surprise. It would have baffled many a thinker who has never bothered to read works of others. She deserved praise because she had derived the variance of the distance-weighted average. Agterberg in 1974, David in 1977, and Journel in 1978 never took the trouble to derive this variance. It’s a bad omen that the distance-weighted average morphed into a kriged estimate on Matheron’s watch. It was Matheron who had failed to derive the variance of this kriged estimate long before geostatistics was hailed far and wide as a new science.

ISO has set the stage to tackle trueness. It did so by issuing a NWIP (New Work In Progress). I am pleased that ISO/TC69/SC6/WG1 has been entrusted with the task. Accuracy (trueness and precision) is way wide of the mark. Trueness (accuracy and precision) reads but a bit better. I would rather work with either Precision and accuracy or Precision and bias. Trueness makes more sense in a court of law. I have worked on a number of ISO Committees since 1974. It would be a senseless task to keep track of trueness. Testing for bias always makes sense. Student’s t-test not only shows what’s biased and what’s not but also gives intuitive measures for statistical risks. I am pleased that ISO never took to kriging and smoothing. Unlike ASTM which went along with geostatistical thinking in 1994. ASTM was set up in 1898 by chemists and engineers. A precursor to CIMMP was set up in 1898. CIMMP’s geostatical peer review process has been blatantly biased since the 1990s.

A smart student of sorts taught at TU Delft in 1958 a seminar on the skew frequency distribution of ore assay values. It was none other than young Agterberg. And did he teach real statistics in those days! Scores of students at the University of Utrecht did indeed grow up with real statistics! Agterberg was no exception. I only found out when I read his 2000 eulogy for Professor Dr Georges Matheron. He brought up that Professor H J de Wijs thought the ratio of element concentration values to be constant regardless of the volume of the block. Here’s ad verbatim Agterberg’s criticism of what Professor H J de Wijs taught at TU Delft in 1958, “…it would be better to apply the conventional method of serial correlation to series of assay values.” Now that was in 1958 Agterberg’s point of view on spatial dependence between measured values in ordered sets. Why then did he swallow Matheron’s assumed spatial statistics with hook, line, and sinker?

When ISO was set up in April 1947 at Paris, France, it was all about nuts and bolts. As a matter of fact, ISO/TC1 Screw heads came first and ISO/TC2 Fasteners was second. Ever since has ISO been setting up a broad range of standards while the world is putting its standards to the test. But I wonder why ISO did err on trueness. Here’s what ISO announced in its Technical Corrigendum 1 on 2005-08-15.

Accuracy (trueness and precision) of
measurement methods and results
Part 5: Alternative methods for the determination of
the precision of a standard measurement method

Every scientist and engineer ought to grasp the properties of variances. Those who don’t should not even try to apply a true t-test for bias. And nobody could do it without counting degrees of freedom. It is an irrefutable fact that a true t-test for bias cannot be applied without counting degrees of freedom. That’s why geologists ought to question the validity of geostatistics. The more so since the author of the very first textbook predicted that “…statisticians will find many unqualified statements…” What David didn’t predict was that he would blow a fuse if somebody did. By the way, keep your copy in a safe place. It may well become a collector’s treasure before this millennium is history. Counting degrees of freedom comes to mind as a topic that does not get the respect it so richly deserves. But I’m getting off my train of thought! Here’s a simple but true test for bias applied to an ancient set of paired data.

Testing for bias plays a key role in science and engineering. Student’s t-test is the par excellence test for bias. The t-test for paired data has always played a key role in my work. A bias between test results at loading and discharge is a constant cause of conflict between trading partners. The question is then whose test results are biased. A matter of concern in 1967 was dry ash contents of anthracite shipments from the mines in Pennsylvania to the port of Rotterdam. I went to the USA and determined that loss of dust during sample preparation was the most probable cause of bias between dry ash contents. I had done time at TUDelft. So, I knew that carbonaceous shale is softer than anthracite, and that hammer mills tend to crush and grind autogenously. That’s why I thought loss of fine dust during preparation of primary samples at loading would cause test samples to show lower dry ash contents at discharge in the Port of Rotterdam.

I know how to fingerprint boreholes. What’s more, Merks and Merks not only know how to fingerprint boreholes but how to derive unbiased confidence limits for metal contents and grades. We have known all of that since Professor Dr Michel David in February 1990 rejected Precision Estimates for Ore Reserves. He was but one of many similarly gifted geostatistical reviewers with CIM Bulletin. The same paper was praised by and published in Erzmetall, October 1991. Moreover, Borehole Statistics with Spreadsheet Software was approved by and published in SME Transactions 2000. I applied this technique to a large set of test results for a gold deposit in Kazakhstan. When I asked my contact at Barrick Gold what he thought of my report, his response was: “It’s worth its weight in gold”. I didn’t charge quite that much on February 9, 1998.

The First Coming of Professor Dr Roussos Dimitrakopoulos to McGill University came to pass in June 1993. He had come all the way from Down Under to chair Geostatistics for the Next Century. It was a bash where geostatistical thinkers of the world had flocked together. They had come to praise Professor Dr Michel David and his 1977 Geostatistical Ore Reserve Estimation. David wrote in his Introduction on page VII that “…statisticians will find many unqualified statements here”. Not a single thinker asked why David had done so. My son and I found some odd gaffes when we studied David’s stuff. That’s the very reason why we wrote Precision Estimates for Ore Reserves. My abstract for The Properties of Variances raised more eyebrows than interest. I have posted on my website both the paper and the review of CIM Bulletin.

Mrs Heather Monroe-Blum, Principal and Vice-Chancellor at McGill University, has not yet responded to my email of November 9, 2010. Neither did Dr Jacques Hurtubise, Chair, Department of Mathematics and Statistics, or Dr Christophe Pierre, Chair, Department of Engineering. I explained why geostatistics is an invalid variant of applied statistics. Here’s what I wrote ad verbatim:

On November 5, 2010 I perused Canada’s University Innovation Leaders. Something struck me as odd at McGill University. Stochastic mine planning is taught by Professor Dr Roussos Dimitrakopoulos at the Department of Mining and Materials Engineering. Stochastic mine planning with kriging variances is at odds with genuine variances in applied statistics as McGill students are taught at Mathematics and Statistics. Here’s what McGill students should know about applied statistics and geostatistics. Applied statistics morphed into geostatistics under the leadership of Professor Dr Georges Matheron, a French geologist-cum-probabilist and a self-made wizard of odd statistics. My 20-year campaign against the geostatocracy and its army of degrees of freedom fighters is chronicled on my blogs and my website.

The First Coming of Dr Roussos Dimitrakopoulos from Down Under all the way to McGill University came to pass in 1993. He had come to chair an International Forum on Geostatistics for the Next Century. The stage for this early forum was set at McGill’s Conference Office on June 3-5, 1993. Geostatistical scholars from far and wide had come to praise Professor Dr Michel David. For it was he who had crafted the very first textbook. His 1977 Geostatistical Ore Reserve Estimation does refer to “the famous central limit theorem”. Even degrees of freedom make a token appearance in Table 1.IV. His work did qualify for support from the National Research Council of Canada (Grant NRC7035). I do have my own copy of his book and have worried a lot about it. That’s why I mailed an abstract on “The Properties of Variances”. In fact, I did send it twice by registered mail. The first was lost and the second rejected. All I wanted to ask was why each and every distance-weighted average AKA kriged estimate did not have its own variance in his 1977 textbook. The more so since one-to-one correspondence between functions and variances is so sine qua non in my work!