Dataset size Part #9 About MS

Dataset size :

To do this - you need to run your experiment with a large sample population. Three throws of the dice are not really enough, hundreds are better and thousands are better still. In the Florida plague example, the sample population was only 22. In statistical terms, 22 is a very feeble number. You can't say a lot with much degree of confidence from a population of this kind of size unless you go for confidence limits way in excess of the traditional 95% and 99% confidence limits.

You need to know what you are looking for before you run the experiment - you need to have predetermined goals.

#1Predetermined goals

Because we know that any set of results with the dice were possible, we cannot look at the results that have already turned up and then say that our hypothesis about the nature of the dice has been tested. This is because already know what has happened. Provided that we make a hypothesis that explains that facts, that hypothesis is bound to remain untested. This is a difficult concept.to get across.

So let me illustrate this with the Florida example. The researchers analysed the lives of the PwMS in the sample population and found that a number of them had Siamese cats. It is almost certain that they found something that these people had in common with eachother but that was very slightly unusual. I'm not saying that owning a Siamese cat is unusual in a wierd way, just that the minority of people in any town are likely to own a Siamese cat.

There are a very great deal of things that are unusual in this way, working as a computer programmer, owning a model railway set, eating bacon for breakfast, wearing nylon vests, growing up on a farm etc. In fact, most of the things that we do are unusual in the sense that a minority of all the people in the world do them.

We all do an awful lot of things - over the course of our lifetimes, we do many hundreds of thousands of things. So if you take any group of 22 people, you will almost certainly find at least two things that they all do which is unusual in the way just described.

The problem comes when you ascribe a causal relationship between those two things. This is because you haven't tested it. We know we can always find such pairings and we know also that they are usually random. If we want to test the hypothesis that they are related, then we must go out and get a new population plus a control group and test the hypothesis on them.
This is one reason why experimental resulted must be always be replicated. That is why RESEARCH needs to keep going and get a drug that will help all of MS people and will not have bad side affects. Because sometimes the side affects are worse than having MS.

----Selective Sampling - Interpretation - cause and effect ---- Last Modified: 01/21/2008 10:11:02

This concludes this blog