The Evergreen State College

Community of Self Program

Correlation (Pearson) information sheet

Last modified: Tue, Dec 3, 1996 9:00 PM PST




Research report is due Thursday, Dec. 12th.
"For Next Time" is due Friday, Dec. 13th if Eval Conf is Monday or Tuesday.
"For Next Time" is due Monday, Dec. 16th if Eval Conf is Wednesday or Thursday.

Goal: Compute 1 inferential statistic, then close your stat book.
If you've got more than one question, you only have to compute the statistic for one. 
 Once you've got one computed, help other people (put your name on the board).  We'll
 help you with more if everyone else is this far (later).  

End:  (from "In the Literature section", p. 517)

A correlation for the data revealed that ________ and __________ were 
(a. significantly / b. not significantly ) related, r = ____, n = ___,
  p (< / >) .05, (a. one tailed / b. two tailed).

If you choose the "<", then you choose "significantly".  
If you choose the ">", then you choose "not significantly".

Blanks:
First blank:	your 1st variable (X's)
Second blank:	your 2nd variable (Y's)
Third blank:	the correlation you compute
Fourth blank:	n

r = 		SP /  Square Root of (SSx * SSY)

One way is to do the following steps:

1. Compute the mean for each variable
2. Subtract each subject's X score from the mean of X's
3. Subtract each subject's Y score from the mean of Y's
4. For each subject, multiple the numbers from steps 2 and 3.
5. Add together the numbers from step 4.  This is SP
6. Square each number you got in step 2.
7. Add up numbers from step 6.  This is SSx
8. Square each number you got in step 3.
9. Add up numbers from step 8.  This is SSY
10. Multiply  SSx  and SSY.
11.  Take the square root of the number in step 10.
12. Divide SP by the number in step 11.  This is "r".
  
YOU'VE COMPUTED YOUR STAT, GOT YOUR "REJECT" or "FAIL TO REJECT"
CLOSE YOUR STAT BOOK

Now, how about trying a graph.  Goal: graph shows your point. Try a 
few different graphs.   In the end you might decide you don't need 
one, or that a table might be better, but look at the data in a few
 different ways first.  


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Made by: Tom Link & Jennifer Kofkin
E-mail:kofkinj@elwha.evergreen.edu
E-mail:linkt@elwha.evergreen.edu
Last modified: Tue, Dec 3, 1996 9:00 PM PST