Correlation, Method of Least Squares, Linear Regression and the General Linear Model - Geomathematics: Theoretical Foundations, Applications and Future Developments

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XX XX

Fig. 4.10 Abitibi copper hindsight study; comparison of copper cells in (a) 1968, (b) 1977 and (c)

2008. Pattern (a) is same as pattern of copper weights in Agterberg et al. ( 1972 ) but for slightly

smaller area; note minor change in areal copper distribution from 1968 to 1977 and no change at all

in copper cell locations from 1977 to 2008. Single X denotes one or more deposits with production

and reserves (Cu) between 1,000 short tons (st) but less than 50,000 tons (t); XX for cells with

50,000

500,000 t (1 st ¼ 0.907 t). In total, the 2008

copper cells contain about three times as much copper as they did in 1968 (Source: Agterberg

2011 , Fig. 2)

500,000 t; XL for cells with Cu

containing one or more copper deposits in the combined data set. The 1968 data set

has three deposits not in Lydon's data base but plotted in Fig. 4.10 , whereas the

Lydon data base contains three Ni-Cu deposits with 0.1 % copper grade not in

Agterberg et al. ( 1972 , Appendix 1) and not plotted in Fig. 4.10 . On average, a

copper cell shown in Fig. 4.10c contains (63/35)

1.80 large copper deposits

but because of localized strong spatial clustering, the frequency distribution of

number of deposits per copper cell is highly positively skewed with one cell (37,8)

in the Noranda mining district containing as many as 11 large copper deposits.

Comparison with Fig. 4.10b shows that nearly all differences between the patterns

in Fig. 4.10a, c date from before 1977. The ten copper cells with most copper are

listed in Table 4.5 .

As mentioned before, new discoveries during the 1970s either were discovered

close to known 1968 deposits or within the areas with relatively high copper

potential outlined in Fig. 4.7 . By 1977, geographical distribution of large copper

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