A–50 Tables and Reference Information
826DEC~1.DOC TI-83 international English Bob Fedorisko Revised: 10/26/05 2:20 PM Printed: 10/27/05 3:09
PM Page 50 of 58
This section contains statistics formulas for the Logistic and SinReg regressions,
ANOVA, 2.SampÜ
ÜÜ
ÃœTest, and 2.SampTTest.
The logistic regression algorithm applies nonlinear recursive
least-squares techniques to optimize the following cost function:
J
c
ae
y
bx
i
i
N
i
=
+
−

ï£




−
=
∑
1
2
1
which is the sum of the squares of the residual errors,
where: x = the independent variable list
y = the dependent variable list
N = the dimension of the lists
This technique attempts to estimate the constants a, b, and c
recursively to make J as small as possible.
The sine regression algorithm applies nonlinear recursive least-
squares techniques to optimize the following cost function:
[]
Jabxcdy
ii
i
N
=++−
=
∑
sin()
2
1
which is the sum of the squares of the residual errors,
where: x = the independent variable list
y = the dependent variable list
N = the dimension of the lists
This technique attempts to recursively estimate the constants a,
b, c, and d to make J as small as possible.
Statistics Formulas
Logistic
SinReg
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