I suggest to pause for a moment, sit back and think about this philosophical question. What are we doing when we are doing statistics? How to embed statistics into the landscape of modern science and engineering? Does the name properly reflect the subject?

I am not looking for short twitter-like answers discussed here. I am more in the search for a detailed well-argued opinions in this spirit.

So, what is your personal opinion?

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    $\begingroup$ This appears to be a purely opinion-based question. Indeed you explicitly say it in your last sentence. That's one of the standard stackexchange reasons to place a post on hold. $\endgroup$ – Glen_b Jun 24 '16 at 0:10
  • $\begingroup$ Well, I am interested exactly in personal opinions :) of experts such as, for example, you. Opinions, that you never see published, but may hear, for instance, in conversations during conference dinners :) Should I remove the question? $\endgroup$ – Kostia Jun 24 '16 at 1:06
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    $\begingroup$ I understand your interest (indeed I share it), but purely-personal-opinion questions are (by design of the founders) not suitable questions for our site, and they have become less acceptable as the site has evolved (you may find a few old threads that survive for historical reasons even though they'd close quickly now). You're free to pursue opinion on chat. Alternatively you might consider whether there's a version of your question more open to answers supportable by facts rather than personal opinion ... ctd $\endgroup$ – Glen_b Jun 24 '16 at 1:59
  • $\begingroup$ ctd... (I suspect that's not possible without a very substantial shift however). If you'd prefer it and you're able to delete, you're free to do so, though if it were me I would not, given someone contributed an answer. If they're happy, then there's no harm in it. $\endgroup$ – Glen_b Jun 24 '16 at 1:59
  • $\begingroup$ @Glen_b I was going to create a questing asking people to contribute examples of counter intuitive problems in probability and statistics. Just would like to double chek with you: would this be considered as an opinion-based question? ("counter intuitive" is somewhat subjective, but often people either agree or disagree on whether something is intuitive or not). $\endgroup$ – Kostia Jun 27 '16 at 7:39

To start with, let me describe my point of view.

What is Statistics?

Opinions vary. In fact, there is a continuous spectrum of attitudes toward statistics ranging from pure theoreticians, proving asymptotic efficiency and searching for most powerful tests, to wild practitioners, blindly reporting p-values and claiming statistical significance for scientifically insignificant results. Even among most prominent statisticians there is no consensus: some discuss the relative importance of the core goals of statistical inference, others comment of the differences between "mathematical" and "algorithmic" cultures of statistical modeling, yet others argue that mathematicians should not even teach statistics. The absence of a unified view on the subject led to different approaches and philosophies: there is frequentist and Bayesian statistics, parametric and nonparametric, mathematical, computational, industrial, applied, etc. To complicate the matter, machine learning, a modern subfield of computer science, is bringing more and more new tools and ideas for data analysis.On top of that, data science, a fancy mixture of statistics and machine learning is becoming more and more popular.

I tend to view statistics as a branch of mathematical engineering that studies ways of extracting reliable information from limited data for learning, prediction, and decision making in the presence of uncertainty. To the best of my knowledge, this view was first expressed by Cosma Shalizi.

Statistics is not mathematics per se because it is intimately related to real data. Mathematics is abstract, elegant, and can often be useful in applications; statistics is concrete, messy, and always useful. The difference between statistics and mathematics is akin to the difference between a real man and the Vitruvian. As a corollary, the proofs are not of paramount importance in statistics. Their main role is to provide intuition and rationale behind the corresponding methods. On the other hand, statistics is not simply a toolbox that contains answers for all data related questions. Almost always, as in solving engineering problems, statistical analysis of new data requires adjustment of existing tools or even developing completely new methods. For example, recent years witnessed an explosion of network data for which most of the classical statistical methods and models are simply inappropriate.


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