Eric Worrall writes;
Mike Whitehorn, chair of analytics at Dundee University, has written a fascinating article on The Register, about why data analysis is always contaminated by the value judgements of whoever is doing the analysis.
According to Whitehorn; “Evidence-based decision making is so clearly sensible because the alternative — making random decisions based on no evidence — is so clearly ludicrous. The “evidence” that we often use is in the form of information that we extract from raw data, often by data mining. Sadly, there has been an upsurge in the number people who move from the perfectly sensible premise of “basing decisions on data” to the erroneous conclusion that “the answer is therefore always in the data”.
All you have to do is to look hard enough for it. This strange leap of non-logic seems to apply particularly to big data; clearly the bigger the data set the more information it must contain.” http://www.theregister.co.uk/2014/10/20/sanity_now_ending_the_madness_of_data_completism/
The article is not about climate change, but it is an excellent explanation of why some data analysis tasks are impossible, using clear examples to illustrate his points, such as a thought experiment of some of the issues you would face if you tried to predict the winner of the next World Cup. One thing Whitehorn is clear about, is that the test of a system is whether it has predictive skill – something which climate models sadly lack. Or as Whitehorn puts it, “WS Brown in Introducing Econometrics defines data mining as: “An unethical econometric practice of massaging and manipulating the data to obtain the desired results.”