barmar, on 2012-February-27, 19:53, said:
The two methods actually produce pretty similar results when the field is evenly split among results. The difference is mostly apparent to outliers.
Of course, the methods give approximately the same results when the field is evenly split among the results. There is also nothing wrong in using medians to
estimate things (life time of a light bulb, amount of food and drinks to be bought before a party, amount of tax you need to pay, ..., or an IMP pair score). Many people do this all the time, but the smart ones are aware that they make an error. Often you don't need to have exact figures. (Does it matter that people drink 2.342643 bottles of wine at my party if I estimated that they will drink between 2 and 3? Either way I will end up buying three bottles.)
- Calculating with medians (or modes) is usually easiest, but it will come with the largest error. If this error is perfectly acceptable, by all means (
) use medians.
- Calculating with averages (more precisely: means), such as Butler, is a little more difficult and will be more accurate. If the calculation that you are performing is linear (IMP scoring is not) you will even get the correct answer: If I know the mean amount of wine that people drink on average, I will be able to tell the total wine consumption by multiplying the mean by the amount of people. However, knowing the mean won't tell me how many people will not be allowed to drive anymore and, therefore, will be sleeping over.
- Calculating with the whole set of results (Cross-IMP) requires more work, but it will give you the correct answer.
Rik
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