Athapascan Indians; Indians of North America -- California
â = [=Y] - [^b][=X]
where X_{i} = ln A for each group with known population and Y_{i} = P
for each known group.
Similarly the estimate of b' is
=S=(X_{i} - [=X])(Y_{i} - [=Y])
[^b]' = -------------------------------
=S=(X_{i} - [=X])^{2}
and of a' is
â' = [=Y] - [^b]'[=X]
where X_i = ln F for each known group and Y_i = P for each known group.
These calculations are shown in table 4.
TABLE 4
_Calculation of Regression Lines Shown in Figure 2_
=================================================================
Fishing Miles
_________________________________________________________________
(X_i - [=X]) (Y_i - [=Y]) (X_i - [=X])(Y_i - [=Y]) (X_i - [=X])^2
-.452 -.027 .012 .204
-.882 -.579 .511 .778
.058 -.483 -.028 .003
.548 .393 .215 .300
.068 -.208 -.014 .005
.658 .905 .595 .433
---- ---- ----- -----
Total. 1.291 1.723
_________________________________________________________________
Area
_________________________________________________________________
(X_i - [=X]) (Y_i - [=Y]) (X_i - [=X])(Y_i - [=Y]) (X_i - [=X])^2
.041 -.027 -.001 .002
-.445 .579 .258 .198
-.514 -.483 .248 .264
.034 .393 .013 .001
.400 -.208 -.083 .160
.484 .905 .438 .234
---- ---- ---- ----
Total. .873 .859
_________________________________________________________________
The results are the following equations, which are shown, together with
the points from which they were calculated, on figure 2.
P = 1.02 (ln A) - 4.06
P = .75 (ln F) - 1.00
Thus, given either the area of a group or the fishing miles of a group
habitat, we may estimate its population. From the diagram in figure 2 it
appears that the estimates based on area have greater dispersion than
those based on fishing miles and are therefore less reliable. This fact
can best be made precise by using the above assumptions to obtain the
confidence intervals for each of the estimates. The confidence intervals
for the area estimates are given by the following formula (Bennett and
Franklin, 1954, p. 229).
_______________________
{1 (X_o - [=X])^2 }
1.02 X_o - 4.06 ± t_[oc]S_a × [Sqrt]{- + -----------------}
{6 =S=(X_i - [=X])^2}
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