| # Although the values associated with any conventional probabilities (P<sub>90%</sub>, ''P''<sub>50%</sub>, and ''P''<sub>10%</sub>) can be read directly from the log probability paper, neither the mode nor the mean is so apparent. These parameters must be calculated. | | # Although the values associated with any conventional probabilities (P<sub>90%</sub>, ''P''<sub>50%</sub>, and ''P''<sub>10%</sub>) can be read directly from the log probability paper, neither the mode nor the mean is so apparent. These parameters must be calculated. |
− | # The mean (or average) is the single best numerical representation of the distribution and is determined approximately by ''Swanson's Rule of approximation''<ref name=Megill_1988>Megill, R. E., 1988, An introduction to exploration economics, 3rd ed.: Tulsa, OK, PennWell Books, 238 p.</ref> as follows: | + | # The mean (or average) is the single best numerical representation of the distribution and is determined approximately by ''Swanson's Rule of approximation''<ref name=Megill_1988>Megill, R. E., 1988, An introduction to exploration economics, 3rd ed.: Tulsa, OK, PennWell Books, 238 p.</ref> as follows: <math>\text{Mean} = 0.3(P_{90%}\text{ value}) + 0.4(P_{50%}\text{ value}) + 0.3(P_{10%}\text{ value})</math> |
| # Must ''all'' distributions be lognormal? A good working rule here is to ''assume'' lognormality, but be willing to modify or adjust the distribution if there is ''legitimate'' evidence (not just wishes or guesses) supporting it. | | # Must ''all'' distributions be lognormal? A good working rule here is to ''assume'' lognormality, but be willing to modify or adjust the distribution if there is ''legitimate'' evidence (not just wishes or guesses) supporting it. |