Analysis of Stack Overflow's Survey of 10K developers

This is some really interesting data. I could spend hours on this site given some interesting things to look at. I really wish SO had included salary in their survey.<p>Some feedback since I see you are the cofounder of statwing:<p>1. I'd really love to be able to share one specific stat/relation with a friend. I found the relationship between "Career / Job Satisfaction and Number of Employees at Company" to be very interesting, and wanted to share just that one with a friend. Either include a share button on each relation, or update the url to reflect exactly what I'm looking at so that if I send it to someone it'll take them to the same page.<p>2. Your front page looks like it was written for data producers. Write it instead for consumers. I would be much more likely to come to your site again and again if it showed something similar to Quora: a list of most popular (by views, upvotes, recency, or ideally a combination of all three) stats. Stuff that a lot of people have found interesting and I will probably find interesting so I can go look for myself.<p>Edit: I just realized statwing is pretty much only for privately analyzing your data. That's too bad. I could see it being a really entertaining site for public data.

From playing around with the data, <i>Stack Overflow reputation</i> was not strongly correlated with <i>compensation</i>. Instead, <i>experience</i> (and naturally <i>age</i>) exhibited a stronger relationship with getting paid.

Properly interpreting this data is hard. For instance, the relation between 'Desktop OS' and 'Compensation' suggests Windows 8 users earn significantly more, on average, than Linux users. However, if you dig a bit further, you find that Linux use is much higher in countries where 'Compensation' is much lower across the board. So the relationship between 'Desktop OS' and 'Compensation' is a proxy for the relationship between 'Country' and 'Compensation', which makes it much less surprising.

"There is a very weak but statistically significant relationship between Owns: iPhone and Using: Node.js"<p>Hipster Hackers.

Ok here's an analysis on job satisfaction that I found interesting.<p>1. very weak relationship to high compensation. Not completely surprising and in-line with much of the research.<p>2. Here's a hard one. No significance of consumer device (tablet, gaming console, etc) EXCEPT for Apple devices (albiet a weak one). All the fanboys are probably nodding their heads but I challenge you to explain it rationally.<p>3. The importance of work/life balance seems to show in the data with weak relationships to job satisfaction but its mostly around hours spent working and commuting. Why is it only a weak relationship?<p>4. Suprisingly, life at work seems to be less related to job satisfaction. With only very weak relationships to things like quality of office space, bureaucracy, quality of workstation, # of meetings, opportunities to work on new tech, and opportunities for growth. I wonder if perhaps the data is skewed by the averages. I wonder what the data would look like if you separated tier 1 developers from everyone else.

I wish there was a way to filter by full-time vs part-time/intern. Filtering by country USA, a plurality of developers under 25 are making under $40,000. I am assuming that a good portion of them are interns.

People in the advertising industry who think their job is very important:<p>53.1%

More exprienced developers spend more time refactoring code? Does that mean that they're working on crappier code, established code bases, or higher end applications where tech debt really matters?<p>Conversely, are the younger guys spending less time because they don't know any better, working on small projects where tech debt isn't a priority, or working on completely new code.<p>My guess it's a reflection of the type of work being done.

What does "non-negotiable" mean? It's positioned between "don't care" and "not very important".

I think I asked this last time I saw a Statwing analysis, but are you guys accounting for multiple comparisons anywhere? The actual p-values are quite robust here, but I can generate some pretty spurious analysis by just running every comparison at once.

I would expect age to be somewhat skewed toward 20-somethings, but not so strongly. Makes me wonder if this is an accurate picture of developers in the US.

This just in-- there is a strong and significant relationship between age and years of experience. Who knew?!<p>Also, job satisfaction and new feature dev!

5k+ using jQuery but only 3k+ using JavaScript?

This is disappointing for me, C# developers tend to make less. Then again, young people tend to make less (definitely causation) and C# developers tend to be young, so maybe there's no causation there. Or maybe there is and that's why older people get out of C# development!