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Posted - 11/03/2006 :  12:35:59   [Permalink]  Show Profile  Send chaloobi a Yahoo! Message Send chaloobi a Private Message
Back to statistics and testing.....

From my own experience, you can tell a lot about a data set if you plot the distribution. If it's normal (bell shaped) then you've likely got a good sample. However, if it's skewed one way or another or if it's all over the place, then there is some problem or bias in the system you're studying. That or your Measurement System is faulty. And that's really what we're talking about here. Is the measurement methodology used in this study impartial?

Typically what's done is a Measurement System Analysis to verify the data collection is impartial, non-biased, etc. That's done before any sample data is even taken. Back end verification that your data is unbiased is first to look at the distribution of the data points. If it's normal (bell shaped) with all center measures equal (mean, median and mode) then you've got a good sample. However, if it's skewed one way or another or if it's all over the place, then you can say there was some problem or bias in the system you're studying (which can be accounted for). That or your measurement system is faulty. Probably there's any number of ways to plot this data and test for normality - by location, by type of death, by whatever....

I did some looking for information on statistical tests for validity of data and came up with this web site which is a huge statistics resource. It's got tons of stuff, so check it out if you're interested in stats.

I browsed through the topics to find some info on what kinds of tests that might apply to data validity, etc. I came up with:

A. Tests for Normality, RE what I was talking about above:

B. This is a technique for determining the reliablity of your data gathering methods (raters in this case would be the groups of doctors doing surveys). They compare data gathered between the 'raters' and even between different sets taken by the same rater, looking for bias.

C. This is apparently a widely used test of data:

D. Bias reduction techniques:

These articles are brief and geared for stuedents of statistics (ie not for the layman). But they give you an idea of what statistics can do and at a minimum they introduce ideas and terms you can use to do further searches.


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