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st: RE: highly skewed, highly zeroed data


From   "Kieran McCaul" <Kieran.McCaul@uwa.edu.au>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: highly skewed, highly zeroed data
Date   Wed, 25 Nov 2009 13:52:32 +0800

...

The skew in the data does not stop you from calculating the mean, nor
does it stop you from calculating a 95% CI around the mean.
Regardless of the skew in the data, the sampling distribution of the
mean will be Normal.



clear *

input time wt
   0  518  
 .25    2  
  .5    3  
   1   15  
 1.5    1  
   2   23  
   3   10  
 3.5    1  
   4   11  
   5   13  
   6    9  
   7    3  
   8   19  
  20   10  
  45    9  
end

mean time [fw=wt]

Mean estimation                     Number of obs    =     647

--------------------------------------------------------------
             |       Mean   Std. Err.     [95% Conf. Interval]
-------------+------------------------------------------------
        time |   1.605873   .2343624      1.145669    2.066077
--------------------------------------------------------------



______________________________________________
Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2701
Fax: (08) 9224 8009
email: Kieran.McCaul@uwa.edu.au

		
______________________________________________
If you live to be one hundred, you've got it made.
Very few people die past that age - George Burns


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Jason Ferris
Sent: Wednesday, 25 November 2009 10:07 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: highly skewed, highly zeroed data

Hi, 
I have tried to find my answer in the statalist repository but nothing
has quite hit the mark.

I would like to calculate a mean and 95% CI of this data - which is
highly skewed and the majority are zeros.

I am aware of adding a constant and the transforming on the log scale
(with antilog) for interpretation.  However after adding a constant to
overcome the zero issue and then transforming on the log scale I am
still left with a highly skewed distribution.  Which gets me no close to
a mean and CI.

PS. As this is survey data I would be most keen for the 'right' answer
to be addressed in svy: terms

Jason

 time (hrs) |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |        518       80.06       80.06
        .25 |          2        0.31       80.37
         .5 |          3        0.46       80.83
          1 |         15        2.32       83.15
        1.5 |          1        0.15       83.31
          2 |         23        3.55       86.86
          3 |         10        1.55       88.41
        3.5 |          1        0.15       88.56
          4 |         11        1.70       90.26
          5 |         13        2.01       92.27
          6 |          9        1.39       93.66
          7 |          3        0.46       94.13
          8 |         19        2.94       97.06
         20 |         10        1.55       98.61
         45 |          9        1.39      100.00
------------+-----------------------------------

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