**CYBAEA Data and Analysis**, and kindly contributed to R-bloggers)

John Kay muses on interpreting statistical data:

Always ask of such data “

what is the question to which this number is the answer?”. “Earnings before interest, tax, depreciation and amortisation on a like-for-like basis before allowance for exceptional restructuring costs” is the answer to the question “what is the highest profit number we can present without attracting flat disbelief?”.

And on the pitfalls of powerful data analysis tools:

When the data seem to point to an unexpected finding, always consider the possibility that the problem is a feature of the data, rather than a feature of the world. […] It is now easy to import data into a computer program without thought. The unwarranted precision of the projected growth in rail traffic – a 96 per cent increase, rather than a doubling – is a clue that the number was generated by a computer, not a skilled interpreter of evidence.

Statistics are only as valid as the sources from which they are drawn and the abilities of those who use them. When I discover something surprising in data, the most common explanation is that I made a mistake.

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