Discussion - Estimate and Incorporation of Metallurgical Data in a Mineralization Model – Technical Papers, MINING ENGINEERING, Vol. 36, No. 8, March 1984, pp. 270-275 – Miller, V.

- Organization:
- The American Institute of Mining, Metallurgical, and Petroleum Engineers
- Pages:
- 1
- File Size:
- 63 KB
- Publication Date:
- Jan 1, 1985
Abstract
The difference of means of milling characteristics by rock and ore type is tested in a statistical manner in the paper. The null hypothesis being tested is that the sample means of two different populations are equal. It is assumed that the null hypothesis is true when performing the test. Because of this, acceptance of this hypothesis leads to the conclusion that the sample means of the two different populations are equal (or there is no significant difference between the sample means), not that the samples come from the same population, as the author asserts. Rejection of the null hypothesis leads to the conclusion that the sample means of the two different populations are not equal. A P value for this test is reported in Table 2 and is incorrectly identified as the probability that the two samples came from different populations. Actually, what was recorded was 100(1 - p) where p is the usual p-value. The usual p-value measures, on a scale of zero to one, the extent to which the data agree with the null hypothesis. It is the probability of observi" a value of the test statistic (Z score) that is at least as contradictory to the null hypothesis as the one computed from the sample data (McClave and Dietrich 11, 1982). The author makes no mention of the fact that were these tests to be conducted together, the chances of determining that the null hypothesis is not true when it is really true are increased considerably (Snedecor and Cochran, 1980). This is a multiple comparisons problem and should be dealt with accordingly. The usual methods involve adjusting the level of the individual tests. Table 2 reports an incorrect 100(1 - p) value in the comparison of concentrate grades for other rock types with .30 to .69% Cu vs other rock types with .70 + % Cu; 86% should be 98.6%. Although the article can be criticized for poor data presentation and discussion of that data, the point the author makes regarding the use of these statistics in the ore reserve estimation process is well taken. It does not appear that inaccuracies in the statistical interpretations have hindered that usefulness.
Citation
APA:
(1985) Discussion - Estimate and Incorporation of Metallurgical Data in a Mineralization Model – Technical Papers, MINING ENGINEERING, Vol. 36, No. 8, March 1984, pp. 270-275 – Miller, V.MLA: Discussion - Estimate and Incorporation of Metallurgical Data in a Mineralization Model – Technical Papers, MINING ENGINEERING, Vol. 36, No. 8, March 1984, pp. 270-275 – Miller, V.. The American Institute of Mining, Metallurgical, and Petroleum Engineers, 1985.