<p>As a beginning user, I would like to give my opinion on this and why <strong>I strongly favour (3)</strong> if it is possible to write such an answer clearly. An example where I learned a lot from reading a "wrong" question is <a href="https://stats.stackexchange.com/q/20836/176202">this one</a> by @gung.</p>

<blockquote>
  <ol start="3">
  <li>Write an answer that essentially explains why the question itself is mistaken, even if such an answer does not answer the question</li>
  </ol>
</blockquote>

<p>In short: When posing a question about how to implement a method, the OP already assumes the method is valid. Of course there are also great questions of the form <em>"Why is it bad to do X"</em>, but people who assume their method to be correct probably do not end up finding such questions if they already exist. </p>

<p>For example, stepwise model selection procedures is still taught in many statistics courses. Answers such as <a href="https://stats.stackexchange.com/a/20856/176202">this one</a>, on what is currently the top question sorted by 'frequent', shed light on topics that are very often misunderstood in statistics. </p>

<p>Similarly, binning continuous variables as you mention in the question is something that I think needs a good explanation why it is bad. This might result in more people wondering how to bin their continuous variable, searching or writing up a question and finding: <em>"Ah, someone else already asked this, let's have a look."</em></p>

<p>In an ideal world everyone would first search for questions related to their method to find out if they are doing the right thing at all, but I think the fact that such questions keep reappearing suggests that many don't. Hence I really appreciate answers such as gung's which not only address a frequent 'problem' on the site, but are also very informative for those searching something along the lines of <em>"How to do stepwise"</em>.</p>

<p>In fact, if there were a convenient way to find these "wrong" questions with great answers, I would enjoy reading them. They are also of great help when teaching students about common pitfalls and fallacies in statistics.</p>

<p>Of course, if such a Q&amp;A already exists, it can be marked duplicate.</p>
