Quote:
Originally Posted by New Era
the problem with Tinordi's link is it shows a weak attempt at normalizing data that is already acknowledged as being faulty. If sampling problems are a result of methodology consistencies the data is considered unreliable. You cannot normalize data that should be excluded from the data set as a result of collection errors. If you do it just further compromises your data.
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So the solution then is to disregard the interpretations of all the data? I think the fairly simple alternative here would be to recognise the rather infinitesimal margin of error when it comes to data collection for shots from one building to the next. Yes, there are flaws in the data collection system, but what the linked beech does help to show is that with regards to this particular item the variances are likely to have no perceivable impact on the results.
Quote:
Originally Posted by New Era
If you believe the data to be accurate, then yes, you may attempt to make an inference. But if the data is questionable, then any inference made is just a guess. Do I really have to explain how bad data can misrepresent the facts and present a skewed picture of the facts?
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No, but what you should be willing to demonstrate is the degree to which the data is actually questionable. How badly skewed are the numbers, and how have you determined this? If you can establish a good basis for your scepticism, then I will concede the point. But so far, you have provided nothing more than anecdotal claims about the degree to which the data is bad, and how dramatically this affects the outcome.