Many of the journals discussed assume a knowledge of statistics. In fact, it is often the statistics that are the crucial issue in a critical review of a research study. And paradoxically it seems that the further we move from the more scientific field of basic science and towards the more “accessible” field of clinical medicine, the statistics becomes more not less complicated.

“Hard” science might involve testing a complex hypothesis with a single complex experiment in a controlled, perhaps in vitro, environment. The experiment might have a few runs, or a few test subjects or perhaps only one. Statistics are all about estimation and sampling, so little if any statistics may be involved after the result is obtained – especially if there is only one result!

Oon the other hand, a clinical medicine study might involve a relatively easy to conceptualise hypothesis and easy measurements but tested on a real life subject where there are myriad other variables over which the investigator has no control. As a consequence, the test may have to be repeated in many different subjects in order to minimise the “noise” of random variabilities and maximise the “signal” of the variable under investigation. With repetition, the “signal” is amplified in an additive fashion, while the “noise” cancels out. Furthermore, in clinical medicine the hypothesis may be more vague; the investigation might involve an empirical study of a number of different factors which might interact with one another. Often the more vague the hypothesis, the more advanced the statistics required to make any sense of the data.

So I am really simply warning the reader, in a rather long-winded manner, that one may find the most advanced statistics lurking behind the abstracts of the most seemingly accessible research, and that probing the authors’ statistical interpretation of their data is sometimes the key to deciding how seriously to take their findings.

With this in mind I have attempted a statistical primer for the non-statistician, perhaps to dip into as a statistical topic comes up in a journal review, or perhaps to peruse in a more thorough manner. The contents link is below:

Primer on Statistics for Non-Statisticians: Introduction and Contents