Earlier today, 8th February here in Gothenburg Sweden, I wrote a comment to Statistical flaws in sciene p-values and false positives, wattsupwiththat.com 2014/02/07
Comment of mine:
To be remembered: (this one from a link on line. Sometimes other words used but the link includes all there is to be remembered BEFORE one go on analysing one’s results)
The strength of the evidence for the alternative hypothesis is often summed up in a ‘P value’ (also called the significance level) – and this is the point where the explanation has to become technical. If an outcome O is said to have a P value of 0.05, for example, this means that O falls within the 5% of possible outcomes that represent the strongest evidence in favour of the alternative hypothesis rather than the null. If O has a P value of 0.01 then it falls within the 1% of possible cases giving the strongest evidence for the alternative. So the smaller the P value the stronger the evidence.
Of course an outcome may not have a small significance level (or P value) at all. Suppose the outcome is not significant at the 5% level. This is sometimes – and quite wrongly – interpreted to mean that there is strong evidence in favour of the null hypothesis. The proper interpretation is much more cautious: we simply don’t have strong enough evidence against the null. The alternative may still be correct, but we don’t have the data to justify that conclusion.Statistical significance, getstats.org.uk page
That said it’s also important to analyse the question oneself has put forward to falsify hypothesis in question. As Vollmer Gerhard wrote 1993, Wissenschaftstheorie in Einsatz, Stuttgart 1993 :
Die wichtigkeit oder Bedeutung eines Problems hängt immer auch von subjektiven, bewer tendens Elementen ab.
Quick English translation: The importance or significance of a problem always depends on subjective, evaluative elements.
In other words one have to remember that no one of us is without having Tendens in our backpack. This means that we have to be careful not to mix black, grey and white alternative nor to ask dependent questuions. Remember that in every analyse of a result that tries to be in accuracy of Theories of Science it’s better to use Chebyshev’s inequality, next in analyse.
While all this might give you more than a hint of a certain type of observation, the ‘fact’ observed in curves that two types of observation interact significantly with it’s other is a total different thing.
If A can be showed to lead up to B in X numbers of studies and at the same time some B lead up to C no nullhypothesis what so ever is enough to prove that A leads to C.
You better use Set of Theory and Number theory on your two variables/curves in order to be able to draw a more than probable conclusion.
The comment I wrote needs further explination:
Think of nine squares of a farmer’s field. On all but the inner one there have been an excavation. Nothing of importance been found. Normally scholars who aren’t scholars of Mathematic tend to believe that it’s proven that there is high likelihood that the inner field should give the same result given it was excavated. That’s wrong.
Inger’s theorem
Fields on land or part of none analysed observations that hasn’t been excavated/evalutated are to be thought as being grey. Not proven to show a significant result nor not proven to do so. theorem presented in my Academic C-essay; Vattenvägarna in mot Roxen i äldre tider, C-uppsats Historia Linköpings Universitet 1993 (English title would be Waterways towards Lake Roxen in older Ages)
This means that one have to have added information in order to be able to draw conclusions that ”holds water”
For example:
Fort/Fortress older than 1000’s from Baltic Sea towards Lake Roxen
On map every destingueshed located fort/fortress (except for two I missed) is marked that can be proven to have been used before 1000 AD. But one need to have datings from archaeologists for every one in order to be able to show that during each period’s peak (Stone Age, Bronze Age, Early resp Late Iron Age, Migration Age, Early Viking Age) the ‘best’ waterway of each period was used. (read due to waterlevels and landrise best waterway to be used) That I did in my essay apart from the extra I had had to analyse, in other words Waterlevels in Oceans and Sea from Mid-Stone Age to 1000 AD. (43 variables I first had to write a computer program for) checking actually known coastline/waterlevel to be able to use the results in Baltic Sea and Baltic Sea’s precursors.
Conclusion: Mathematic Statistic isn’t as easy as many scholars believe. It’s never enough only to use Null-Hypothesis.
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