Barnard’s views on statistical education (from

I really enjoy reading Deborah Mayo’s blog.   I don’t really understand enough about the underlying philosophy – and even gently reading about ideas such as Popper asking for severe challenges (rather than out and out falsifiability) bring this home.   I guess one reason for the blog was to practice articulating ideas I’m not so comfortable about but use all the time.

But I’ve just seen a post which quotes from George Barnard:

[I]t seems to be useful for statisticians generally to engage in retrospection at this time, because there seems now to exist an opportunity for a convergence of view on the central core of our subject. Unless such an opportunity is taken there is a danger that the powerful central stream of development of our subject may break up into smaller and smaller rivulets which may run away and disappear into the sand.

I shall be concerned with the foundations of the subject. But in case it should be thought that this means I am not here strongly concerned with practical applications, let me say right away that confusion about the foundations of the subject is responsible, in my opinion, for much of the misuse of the statistics that one meets in fields of application such as medicine, psychology, sociology, economics, and so forth. It is also responsible for the lack of use of sound statistics in the more developed areas of science and engineering. While the foundations have an interest of their own, and can, in a limited way, serve as a basis for extending statistical methods to new problems, their study is primarily justified by the need to present a coherent view of the subject when teaching it to others. One of the points I shall try to make is, that we have created difficulties for ourselves by trying to oversimplify the subject for presentation to others. It would surely have been astonishing if all the complexities of such a subtle concept as probability in its application to scientific inference could be represented in terms of only three concepts––estimates, confidence intervals, and tests of hypotheses. Yet one would get the impression that this was possible from many textbooks purporting to expound the subject. We need more complexity; and this should win us greater recognition from scientists in developed areas, who already appreciate that inference is a complex business while at the same time it should deter those working in less developed areas from thinking that all they need is a suite of computer programs.

Apparently the comments were made around 1981 and published in a monograph around 1985.   I wonder how many such books have been written since then that have really thumbed their nose at his points.   And I must go away and check whether he was considering less formal issues such as appraising the representativeness of a particular (real) sample to the population it purports to represent.

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