<p>When a senior CV participant comments, “CV is a statistical blog,” what does this mean for the community? How is this to be interpreted? A literal interpretation might suggest that only those questions with an unambiguously theoretical statistical stance are appropriate. Obviously, this isn’t true as there are many queries being accepted with concerns that are applied or business related, with a minimal theoretical component. Not only that, given the apparent level of many OPs' statistical literacy, a purely theoretical response might provide an answer but would it be appropriate if it weren’t understood?</p>

<p>On the face of it, it would appear that many CV participants have a clear idea of the kinds of questions and issues CV should handle. For instance, questions that are mostly concerned with programming and/or specific software packages are usually relegated, e.g., to Stack Overflow -- but by no means all. Many, many questions get through that are mostly about statistical software, its implementation and idiosyncrasies. Responses, too, will include programming tips. Similarly, questions that may have a quantitative component but are more heavily content weighted towards specific academic silos such as economics or finance have a higher probability of getting reposted to one of those SE groups. By the same token, inadequately phrased and/or naive questions have a much greater likelihood of being put on hold regardless of their statistical content or value. And so on. The point is that, while there is an appearance of community clarity in terms of the questions that are accepted (or not),  the fact is that there can be considerable ambiguity and leeway in these community decisions. </p>

<p>So, would questions concerned with the history of statistics be appropriate? For instance, what about questions taken from a book like Crosby’s <em>The Measure of Reality: Quantification and Western Society 1250-1600</em>? Is there a clear line between statistics, machine learning, AI or information theory? Are wider controversies such as ongoing debates about the “scientific method” appropriate? How about questions concerned with the overlap and triangulation of qualitative (idiothetic) and quantitative (nomothetic) methodologies? What about issues crossing the blurred line between philosophy and statistics? Deborah Mayo’s blog <a href="https://errorstatistics.com/" rel="nofollow noreferrer">https://errorstatistics.com/</a> is an example of this. Would cultural anthropological issues as embodied in a book like Chrisomalis’ <em>Numerical Notation</em>, which reviews the earliest cultural origins and evolution of numeracy, be appropriate? </p>

<p>Just wondering if there is any clarity in the community on these things as they're not clear to me.</p>
