The methods we describe all follow the general strategy of handling imperfect reproducibility by formalizing scientific questions in terms of statistical models, where relevant aspects of variation are described using probability. We aim not only to provide a succinct overview of useful techniques, but also to emphasize the importance of taking this fundamental first step, of connecting models with questions, which is sometimes overlooked by non-statisticians. More specifically, we emphasize that (i) detection of synchrony presumes a model of spiking without synchrony, in statistical jargon this is a null hypothesis, and (ii) quantification of the amount of synchrony requires a richer model of spiking that explicitly allows for synchrony, and in particular, permits statistical estimation of synchrony

]]>Implicit in the guidelines for writing Ten Simple Rules [1] is “know your audience.” We developed our list of rules with researchers in mind: researchers having some knowledge of statistics, possibly with one or more statisticians available in their building, or possibly with a healthy do-it-yourself attitude and a handful of statistical packages on their laptops. We drew on our experience in both collaborative research and teaching, and, it must be said, from our frustration at being asked, more than once, to “take a quick look at my student’s thesis/my grant application/my referee’s report: it needs some input on the stats, but it should be pretty straightforward.”

There are some outstanding resources available that explain many of these concepts clearly and in much more detail than we have been able to do here: among our favorites are Cox and Donnelly [2], Leek [3], Peng [4], Kass et al. [5], Tukey [6], and Yu [7].

Every article on statistics requires at least one caveat. Here is ours: we refer in this article to “science” as a convenient shorthand for investigations using data to study questions of interest. This includes social science, engineering, digital humanities, finance, and so on. Statisticians are not shy about reminding administrators that statistical science has an impact on nearly every part of almost all organizations.

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