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flyingbird267

1 Posts

Posted - 07/30/2011 : 5:32:47 PM

Hi,ALl,
I was using origin to do a linear fitting of my data, the results are:
Y = A + B * X

Parameter Value Error t-Value Prob>|t|
---------------------------------------------------------------------------
A -0.17357 0.14036 -1.2366 0.26244
B 0.89668 0.00236 380.6276 <0.0001
---------------------------------------------------------------------------

R R-Square(COD) Adj. R-Square Root-MSE(SD) N
---------------------------------------------------------------------------
0.99998 0.99996 0.99995 0.15267 8
---------------------------------------------------------------------------

Parameter LCI UCI
---------------------------------------------------------------------------
A -0.51703 0.16988
B 0.89091 0.90244
--------------------------------------------

because for A, P(Prob>|t|)=0.26244, if I set my significance as 0.05, doe it mean that I should reject the null hypothesis or should I just reject this parameter A but accept B?

thanks,
t

Sam Fang

293 Posts

Posted - 08/02/2011 : 05:39:01 AM

Origin's P(Prob>|t|) is used to perform a t-test on each parameter to see whether its value is equal to 0. So in your case, you should just accept the null hypothesis A=0 and reject the null hypothesis B=0.

For more information, see the page:
http://www.originlab.com/www/helponline/Origin/en/UserGuide/The_Fit_Results.html

Sam
OriginLab Technical Services

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