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(This article was first published on <strong><a href="https://edwinth.github.io/blog-new-things/"> That’s so Random</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Great effort has recently been made to encourage also the not-so-experienced to jump into the water and blog about data science. Some of the community’s hot shots gracefully draw attention to blogs of first-times on twitter to give them extra exposure. Most of the blogger newbies write about an analysis they did on a topic they care about. That sounds like the obvious thing to do. However, I think there is a second option that is not considered by many. That is writing about a topic you just learned. This might seem strange, why would you want to tell the world about something you are by no means an expert on? Won’t you just make a fool of yourself by pretending you know stuff you just picked up? I don’t think so, let me give you four reasons why I think this is actually a good idea.</p>
<h2>It forces you to study deeply</h2>
<p>One of the challenges of learning new aspects about R or data science in general on your own, is that there is no pressure to fully study something other than intrinsic motivation. Combined with a million other things to do in your life, this results all too often in picking up the new thing haphazardly. Revisiting the topic time and time again and leaving yourself with this nagging feeling that you never finish it. By blogging about it, you all of sudden have a great motivation to explore the topic inside out. When you write about it you want to make sure you have covered the most important material there is on the topic and you will not rest until you grasp most of it. As a result you will have a more profound understanding and you will be a more satisfied learner.</p>
<h2>You understand other learners</h2>
<p>Because you only just learned yourself, nobody has a better feeling about the challenges of grasping the topic. A seasoned expert does not only forgets the challenges she had when she was learning, she probably forgets it was a challenge in the first place. Here is Dave Robinson creating awareness for this fallacy</p>
<blockquote class="twitter-tweet" data-lang="en">
<p lang="en" dir="ltr">When teaching, be careful not to mix up &quot;I learned this a long time ago&quot; with &quot;This is simple&quot;<a rel="nofollow" href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw" target="_blank">#rstats</a></p>
<p>— David Robinson (@drob) <a rel="nofollow" href="https://twitter.com/drob/status/722806375005302785?ref_src=twsrc%5Etfw" target="_blank">April 20, 2016</a></p></blockquote>
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<p>By reflecting on your journey of picking up the new thing, you are most likely a more thorough and compassionate teacher than the long time expert.</p>
<h2>You draw attention of experts</h2>
<p>You might think experts couldn’t care less about some newbie getting his feet wet. You are wrong. R community members care deeply about what others do and they provide feedback in a constructive way. Even, or maybe especially, when you are at the beginning of a path they have already completed. When I published a blog on <a rel="nofollow" href="https://edwinth.github.io/blog/nse/" target="_blank">NSE</a>, I got several experts getting back to me within a day. They pointed out to me that I was putting way too much emphasis on a detail in NSE, which distorted the whole picture. As a result the blog post got better (I adjusted it) and my knowledge became more profound.</p>
<h2>You train in being wrong</h2>
<p>So, the NSE blog I worked on for quite some time still had a couple of significant flaws. Experts pointed this out publicly to me (in the blog’s Disqus and on twitter) and this was a great thing. The longer I work as a data scientist, the more I begin to value that being wrong is a skill one should actively develop. Sounds strange? Let me explain. Whether in blogging or in daily work, one’s objective should be to bring as much insight as possible. This is not the same as being right all the time. The latter is the goal of your ego, and the ego has its own agenda. Typically, wanting to be always right leads to withdrawing and postponing, because you are still unsure of $x$ or you haven’t completely figured out $y$ yet. As a result you keep chewing on it, meanwhile (collective) insight doesn’t grow. Of course you want to do your work thorough, I am not encouraging sloppiness or laziness here. Rather, when you have done your best, by all means get it out in the open and let others shoot at it. Your ego will get a few blows now and then, but that’s fine, it better gets used to it. Blogging in this way is a perfect practice for publicizing stuff you haven’t totally figured out yet and experiencing what it is like to be publicly wrong from time to time.</p>
<p>I hope you will consider writing blog posts about stuff you only just learned about. It is a great way to grow and I will certainly keep doing it!</p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://edwinth.github.io/blog-new-things/"> That’s so Random</a></strong>.</div>
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