HP 48gII Graphing Calculator Manuel d'utilisateur Page 621

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Vue de la page 620
Page 18-50
Suppose that we have n paired observations (x
i
, y
i
); we predict y by means of
y = a + bx, where a and b are constant.
Define the prediction error
as, e
i
= y
i
-
y
i
= y
i
- (a + bx
i
).
The method of least squares requires us to choose a, b so as to minimize the
sum of squared errors (SSE)
2
11
2
)]([
i
n
i
i
n
i
i
bxayeSSE +==
==
the conditions
0)( =SSE
a
0)( =SSE
b
We get the, so-called, normal equations:
==
+=
n
i
i
n
i
i
xbnay
11
===
+=
n
i
i
n
i
i
n
i
ii
xbxayx
1
2
11
This is a system of linear equations with a and b as the unknowns, which can
be solved using the linear equation features of the calculator. There is,
however, no need to bother with these calculations because you can use the
3. Fit Data … option in the ‚Ù menu as presented earlier.
____________________________________________________________________
Notes:
a,b are unbiased estimators
of Α, Β.
The Gauss-Markov theorem of probability indicates that among all
unbiased estimators for Α and Β, the least-square estimators (a,b) are the
most efficient.
____________________________________________________________________
Vue de la page 620
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