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 Statistics question
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Posted on 02-03-11 9:06 PM     Reply [Subscribe]
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 I have been working on comparing a set of data and can't figure it out. I think it is pretty simple but I am really bad on statistics. I would really appreciate if someone out there could help.
sample Exp A Exp B
1 1.2 1.4
2 .5 .4
3 2.5 2.5
4 .8 .8
5 1.5 1.4
6 2.0 2.0
7 1.5 1.5

I need to prove with some statistical  terms that Exp A and Exp B can can produce same results. What Stat term can i use to compare the data? I have a total of 40 samples with similar results as above.
Please Please help.
Thanks in advance

 
Posted on 02-03-11 9:58 PM     [Snapshot: 25]     Reply [Subscribe]
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 i am not a statistician  so this may be incorrect ..  this may be ur starting point ....

if I were you I would do z-test based on two sample..with H0 : u1= u2 and H1: u1!=u2....z test because number of samples > 30... just a suggestion...sajha statistician may suggest u more!!!
 
Posted on 02-03-11 10:43 PM     [Snapshot: 56]     Reply [Subscribe]
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 If you are trying to prove that mean of A =Mean of B, then you can use Two-sample Independent T-test.. 
Last edited: 03-Feb-11 10:43 PM

 
Posted on 02-04-11 12:23 AM     [Snapshot: 96]     Reply [Subscribe]
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T test is the best one as. n>30

 
Posted on 02-04-11 9:51 AM     [Snapshot: 160]     Reply [Subscribe]
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 for independent sample use two-sampled t-test; if not use paired t-test; u can run those test easily on minitab or spss
 
Posted on 02-06-11 2:26 PM     [Snapshot: 242]     Reply [Subscribe]
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I got this results and it may be helpful. (T-test result.)

The TTEST Procedure 

group        N      Mean   Std Dev   Std Err   Minimum   Maximum 

a            7    1.4286    0.6824    0.2579    0.5000    2.5000

b            7    1.4286    0.6993    0.2643    0.4000    2.5000

Diff (1-2)             0    0.6909    0.3693 

group       Method             Mean     95% CL Mean      Std Dev 

a                            1.4286    0.7974   2.0597    0.6824

b                            1.4286    0.7818   2.0753    0.6993

Diff (1-2)  Pooled                0   -0.8047   0.8047    0.6909

Diff (1-2)  Satterthwaite         0   -0.8047   0.8047 

group       Method           95% CL Std Dev 

a                            0.4398   1.5028

b                            0.4506   1.5399

Diff (1-2)  Pooled           0.4955   1.1405

Diff (1-2)  Satterthwaite

 Method           Variances        DF    t Value    Pr > |t| 

Pooled           Equal            12       0.00      1.0000

Satterthwaite    Unequal      11.993       0.00      1.0000 

              Equality of Variances 

Method      Num DF    Den DF    F Value    Pr > F 

Folded F         6         6       1.05    0.9542



Last edited: 06-Feb-11 05:03 PM

 


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