•The regression formula is y = A-xB (lny = lnA +Blnx). Enter both data x and y
as logarithms (In).
•Estimated values x, and y based on the regression formula can be calculated
using the following formulas:
- a R - / In y - InA \
y = A*xB x=exp(
-------
-
------
J
•Correction is performed the same as in linear regression. Constant term A is
obtained by B |e 3 ® B ( l l , estimated value y is obtained by Q3 * B ® ® B
gg(Ans)(I§, and estimated value x is obtained by fin] vliiff|ff1HlsHiFf||^|^|pE). Ex,
Ex2, Ly, I <y2 and Lxy are obtained by Elnx, E(lnx)2, Elny, E(ln^)2 and Elnx-lny
respectively.
■ Power regression
Example
Operation
Display
xi
yi
28
2410
30 3033
33
3895
35 4491
38 5717
The data in the above table
can be used to obtain the
terms of the regression for
mula and the correlation
coefficient. Based on the
regression formula, estimated
value y can be obtained for
x/=40, and estimated value x
can be obtained for yi= 10 0 0 .
S B
fSHÎFï] fScll flxil
(Clears memory)
O 32 8S E Q 3241O 0 3)
03 3 0 ® 0033033(13
03 33 ® 003 3895 (dt)
Q3 35 ( 3 [T][]34491 (dt)
038® 0 0 3 57 1 7 (5 3
(Constant term A)
(Regression coefficient B)
iSHiFTlfBlfixi]
(Correlation coefficient r) |shift| f~~F~] fixi]
( y when xi = 40)
0 3 4 0 ® ® (I^ ® (I3 ® li)
(x when yi= 1000)
0 3 1 0 0 0 ® ® ®
m n i& n m
3.33220451
3.401197382
3.496507561
3.555348061
3.63758616
0.2 388010829
2.771866148
0.9989062562
6587.674743
20 .26225659
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