Ian,

Paige did a great job of describing a simple t-test for comparing means from
two different populations.  However, I would like to add that t-tests could
be also used to compare, for example, one group before and after taking a
test via the paired t-test.  The paired t-test compares the differences
between the variables from zero.  

Jeff
---------------------------------------------------------------
Jeff Dang, MPH
Statistician
UCLA Cousins Center for Psychoneuroimmunology
(Affiliated with the Neuropsychiatric Institute and
Department of Psychiatry and Biobehavioral Sciences)
300 UCLA Medical Plaza, Room 3148
Los Angeles, CA 90095-7057
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-----Original Message-----
From: Paige Miller [mailto:[EMAIL PROTECTED] 
Sent: Tuesday, January 27, 2004 5:30 AM
To: [EMAIL PROTECTED]
Subject: Re: [edstat] Stats - is this a t test problem?

Iain Toft wrote:
> I'm no stats expert but would like to solve the following problem.
> 
> Given two sets of scores...
> 
> S1 = [38.37388112, 38.37471969, 38.40682618, 38.37863674, ...,
> 38.39506964]
> S2 = [22.40683282, 22.23267916, 22.08881316, 24.96633041, ...,
> 21.8635192]
> 
> I'd like some statistical evidence to show the scores attained in S2
> are inferior to those in S1. I can show the mean,min,max,stdev but
> would like something with a little more clout.
> 
> Each score in S2 was obtained in the same trial as S1 (that is the
> scorer in S2 was competing against and in the same game/trial as the
> scorer of S1). In this example S2 is clearly inferior in score,
> however for other examples the difference is less prominent (in terms
> of mean). How can I determine if scorer S2 is inferior to S1, from
> what I can fathom out I need some kind of t test?
> 
> There are 50 trials.
> 
> Obvious two questions...
> 1) What is a t test?

In layman's terms, a t-test compares the means of the two groups to 
see if the difference could arise via random chance. You have to 
assume that the data is approximately normally distributed in order 
to use a t-test.

> 2) How do I interpret the results?

Most software packages output a p value for the t-test. If you wish 
use a type I error of 5%, then if the p value is less than 0.05 then 
you would decide that the two means are significantly different. 
(The type I error of 5% indicates that you could be mistaken 5% of 
the time where the means are actually the same but appear different 
via the t-test). Otherwise you conclude the means are not 
significantly different.

But ... I strongly suggest you check out a basic statistics textbook 
and read up on this further.


-- 
Paige Miller
Eastman Kodak Company
paige dot miller at kodak dot com
http://www.kodak.com

"It's nothing until I call it!" -- Bill Klem, NL Umpire
"When you get the choice to sit it out or dance, I hope you dance" 
-- Lee Ann Womack

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