You might use something like a Q-Q plot to see which gives you the closest to a 
normal distribution. David Howell's "big" textbook shows you how. 

Chris
.......
Christopher D Green
Department of Psychology
York University
Toronto, ON M6C 1G4

[email protected]
http://www.yorku.ca/christo

> On Nov 11, 2013, at 7:26 PM, Michael Britt <[email protected]> wrote:
> 
> Thanks for all these suggestions.  I've been thinking of trying all or most 
> of them. I assume that I would get slightly different results, so let me ask 
> this: what criteria would you use to determine which transformation gave the 
> best result?  Would it be the one with the least amount of skew/most normal 
> in distribution?
> 
> 
> Michael A. Britt, Ph.D.
> [email protected]
> http://www.ThePsychFiles.com
> Twitter: @mbritt
> 
>> On Nov 11, 2013, at 7:04 PM, Jim Clark <[email protected]> wrote:
>> 
>> Hi
>> 
>> People have been noting various transformations, depending on reversing or 
>> not the original.  In essence many common transformations can be 
>> conceptualized as the original scores raised to various powers, with the 
>> powers being greater than or less than 1.
>> 
>> x^-1 = reciprocal 1/x
>> x^~0 = logarithmic
>> x^.5 = square root
>> x^1 = original
>> x^2 = ...
>> 
>> I'm mostly used to thinking of these in terms of various non-linear 
>> relationships (powers < 1 compress upper end, powers > 1 expand upper end), 
>> but some of these will increase skewness and others will decrease it, 
>> depending on the direction of skew. Possible to experiment with them to 
>> observe effect.
>> 
>> Perhaps also worth plotting some of the relationships you are interested in?
>> 
>> Take care
>> Jim
>> 
>> Jim Clark
>> Professor & Chair of Psychology
>> 204-786-9757
>> 4L41A
>> 
>> -----Original Message-----
>> From: Christopher Green [mailto:[email protected]] 
>> Sent: Monday, November 11, 2013 5:31 PM
>> To: Teaching in the Psychological Sciences (TIPS)
>> Subject: Re: [tips] What to do with skewed data
>> 
>> Michael, 
>> 
>> There are couple of standard ways to transform skewed data. Invert the data 
>> (subtract each datum from one greater than the highest value) so that the 
>> skew is positive. Then, Depending of the strength of the skew, do a square 
>> root or logarithmic transformation. Alternatively, don't invert it and take 
>> the reciprocal (1/x) of each datum).
>> 
>> Chris
>> .......
>> Christopher D Green
>> Department of Psychology
>> York University
>> Toronto, ON M6C 1G4
>> 
>> [email protected]
>> http://www.yorku.ca/christo
>> 
>>> On Nov 11, 2013, at 1:01 PM, Michael Britt <[email protected]> 
>>> wrote:
>>> 
>>> I did a survey which asked respondents how satisfied they are in their 
>>> current (romantic) relationship on a 1=10 point scale (where 10="very 
>>> satisfied).  While there was some variation, not surprisingly, the results 
>>> are strongly negatively skewed.  That makes sense - most people are 
>>> probably satisfied with their relationships or they would leave the other 
>>> person (or there's some form of cognitive dissonance going on, but that's 
>>> not my question.
>>> 
>>> No matter how big the sample size (mine was 160 respondents) I assume 
>>> you'll always get a skewed distribution on a question like this so wouldn't 
>>> I be breaking the normalization assumption if I were to do correlations 
>>> using these results?   I assume I could either do:  a) do some kind of 
>>> transformation - but I've never done one before so I’m not familiar with 
>>> it, or b) recode the data into 3 categories (perhaps 1-5 is low 
>>> satisfaction, 6-7 is moderate and 8-10 is high) and do a chi-squre instead 
>>> of a correlation.
>>> 
>>> Any thoughts?  Appreciate it.
>>> 
>>> Michael
>>> 
>>> Michael A. Britt, Ph.D.
>>> [email protected]
>>> http://www.ThePsychFiles.com
>>> Twitter: @mbritt
>>> 
>>> 
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