Results of The Hacker Survey | Hacker News Reader

Results of The Hacker Survey

davelyon.net

107 pointstialys57 comments

Six people expect to make negative income this year. Highest incomes are 110M, 98M, 68M, 25M, and 10M (watch out, that last guy took the survey 6 times with bad data).

In the bell curve of "# of years in industry", there are spikes at 10, 12, 15, and 20 -- looks like people rounding.

27% work 40 hours a week. 15% work 50, 10% work 45, 9% work 60, 4% work 35 and 30.

Unemployed hackers are very much more likely to be single (compared to the ratio for all types of employment).

I can see no noticeable correlation between hours worked and expected income.

Mirror: http://defunkt.github.com/hacker-survey/

CSV: http://defunkt.github.com/hacker-survey/data.csv

Mirror: http://go.cleverinnovative.com/hacker-survey.htm CSV: http://go.cleverinnovative.com/data.csv

Thanks for posting the data/results. Only 2% of the respondents are female. Wow.

Why was this voted down? I was fairly shocked too. I mean, I know we're in the minority at HN but not by this amount.

Not sure what conclusion you can draw from that - it was a self-selected sample. For example I didn't vote because of the non-existent "academia/research" option.

I think if you wanted to get a better handle of how many women are in HN, a poll entitled "Are you female" with the options of yes-no-it's complicated- will give you better traction.

> I think if you wanted to get a better handle of how many women are in HN, a poll ...

You mean: http://news.ycombinator.com/item?id=749617 ? There, female was about 6%.

Both groups are self-selected, though one of the samples is larger. But I've no reason to doubt the numbers--they seem to be in the right ballpark. In a competitive, technical community like this one, 2-5% women is about what experience tells me to expect. Fighter pilots are a similar, if more extreme, example: http://userpages.aug.com/captbarb/fighters.html

The phenomenon simply is what it is -- I do not know or speculate on the cause. But I find it fascinating that many people feel compelled to quickly invent stories to explain it away. A little encounter with heresy seems to provoke a defensive rush into mythology.

I think a little cognitive dissonance, a little acceptance of heretical fact, a little uncomfortable admission of ignorance, is good for intellectual hygeine; I welcome and cherish odd little phenomena like this, even if--in fact, especially because--they run so counter to my beliefs and expectations.

Not sure what the point you are trying to make - there is a huge difference between 2% and 6% (factor of 3 to be precise). I personally would think it would be 5% at least, so I chose to believe the poll that confirms my preformed opinion :-)

It's probably an overestimate too, because if you look at the dataset a lot of the 44 women are fake (i.e. have improbable ages such as 407,407,99,95 and are pre-high schoolers). People filling out the survey for the lulz would choose as different a profile from the typical HN-er as they could, and that includes making a female respondent.

Will you remove some of the obvious fake outliers from the data set? eg. Line 338 on the .csv file is a 99 year old female self-employed, pre-high schooler with 10+ kids working 140 hours per week and earning $1M per year. Sounds a little suspect to me...

Not to mention the 22 year old student who completed the questionaire 4 times and has 70 years of experience, works negative hours and earns $100M.

Or the divorced 407 year old female with 700 years of experience and 8 kids.

I decided not to filter the data in the interest of giving anyone the ability to use the exact data set I received. For my personal use, yes, I removed the bad data. But as far as giving out the csv, I thought it made more sense to give people the full set and let them decide (honestly, some people are fishy, but not obviously fake... so it'd be hard to be fair).

I wonder what the =SUM() of the yearly wage is after all the 'for the lulz' posts are filtered. Kinda curious what percentage of the US GDP the HN readership is :)

With the highest earners, 451M. With the top 5 earners (The 5 people over 5M, lulz or not) excluded: 145M.

http://www.wolframalpha.com/input/?i=0.00318+percent+of+1415...

The CSV file is wonderful. Now I know (among numerous other things), how many people took the survey before me.

My line in the survey can be defined by surprisingly few fields.

Me too. The first thing I did was try to find my record. It was easy because my salary figure was fairly unique.

It wouldn't surprise me in the slightest if your Age, Salary and hours are unique in the table. In fact, I'm relative certain that any two of the numerical fields (family excluded, since so many people had 0) would uniquely identify you, or at least limit it to on a handful of individuals. The concept of "Anonymous data" is largely non-existant; if you know who you're looking for in a table of anonymous data, you can usually find them.

Hmm. I whipped up a quick python script to test this theory.

  Age,Hours Wrkd,Income was unique ~89% of the time
  Age,Hours Wrkd, Yrs in industy,Income was unique 97% of the time
  Age,Education,Hours Wrkd,Income was unique 94% of the time
  Age,Education,Hours Wrkd,Yrs in Industry,Income was unique 98% of the time

Here it is if anyone wants to play with it. http://paste.pocoo.org/show/136649/

91% of the people that answered attended college. Can we stop with all the "College is useless" submissions now?

Could you please explain this logic? Wouldn't ~90% of us attending college, then seeing its effects, qualify us to comment on the topic?

You're telling the, at most 9% of the rest of us how useless it is. I just don't think it really contributes anything.

By that logic, all of the linux zealots out there should stop encouraging people to use linux since all the linux people already use it.

Is that about right?

We're telling the other 9% "Hey, guys, learn from our mistakes! Have a nice day!".

I guess 91% of us are saying "Don't sweat the small stuff such as a degree". However, I wish unlearning the college stuff would have been as easier as a switch to linux :)

I wish getting the money that I spent back would have been as easy as switching to linux.

Oh, idea, OPEN SOURCE SCHOOLING!

This would only be correct if Linux users made up 91% of the computing world.

It's like if there were articles still posted about how people should get a monitor which displays at a higher resolution than 800x600.

you have exactly the same amount of information to compare as someone who did not go to university before entering their career.

Hackers appear to have a startlingly low divorce rate.

I think they're just younger than the average divorcee.

perhaps they are more adapt at finding bugs and implementing fixes in all realms of their lives?

"I want a divorce.":

"Hold up, let's backtrack and work this through step by step to see if we can isolate this bug."

Yeah and unfortunately there comes a time when you have to admit that the entire premise of the project was flawed and it's time to liquidate and start-up a new.

I was looking at the guys that make 100k+. It seems that there is a correlation between having a girlfriend/wife and making more money. I'm wondering why? Doesn't having a girlfriend/wife take some more of your time when you could do some coding?

P.S. Wow. I've always thought that this is a very vibrant community and full of intelligent people. It seems I was right. But man even if I'd wish I just can't read all the comments and everything in here, and I'm sure there many worth reading.

A few correlations for your first point:

* Incentive to earn more - esp if we're looking at averages, the $0 startup guys will drag down the singles category.. The married people will likely be after a paycheque of some sort

* Age. - There's usually a link between age and income - and i'd guess at a link between age & partner status..

* Just realised that the raw data is actually there - so I shouldn't be guessing... Haven't got time this second to go through it - I'll try later..

According to stereotype, the causality flows the other way, and having more money is likely to get you a girlfriend or wife. I suspect the stereotype is somewhat wrong and that more money leads to more free time, which leads to more friends and fun activities, which leads to a girlfriend or wife.

The stereotype is not wrong at all. Women are attracted to resources, and this is well established both in humans and in non-human animals. The reason is because women bear most of the inherent costs of child rearing (9 months gestation, breastfeeding, etc). However, providing sperm is not a very costly endeavor. Since females can afford to be choosy (that is, there are many males willing to spend the low cost of a load of sperm or two) they'll choose males with resources, all things being equal. Theoretically this male will lessen the inherent cost to the female by perhaps providing her with food during pregnancy and breastfeeding as well as for the child after it's weaned.

In some birds and mammals, females will choose males that have a bigger or better territory. In some cases, if a male has an especially big territory, the male will attract more than one female. (Emlen S. & Oring, L. 1977. Science 197 , 215-222)

In insects, which tend to not have bi-parental care, this is usually in the form of a "nuptial gift" which is basically a nutritious package that comes along with the sperm (Vahed, K. 1998. The function of nuptial feeding in insects: A review of empirical studies. Biol. Rev, 73:43-78.)

I agree too that women are attracted among other things (celebrity,intelligence, etc) to resources. I would be more specific and mention financial resources nowadays.

I don't mean to be sexist, but having a wife gives you more free time, not less.

You have the workload of a house divided into two instead of one. Even if your wife works it still ends up on the plus side.

It's not like you can code 24/7, you have to have some downtime. No reason not to spend that time with someone else.

Great job!

You must know us as well as we know ourselves because you included the raw data. For a hacker, this is a starting point, not a result. I can't help myself; I've already started my mini-project of building my own data base and reports from your data. Thank you!

(I'm curious what the 407 year old female and 7,000 year old male do to take care of themselves :-)

I hope you'll send me a link to your results. I'm too busy with classes to do much, but I'd love to see some deeper information. I'll be posting my machine learning results in a few weeks as well.

Yep, thank you very much for releasing the raw data too. I've just been playing with it a little, but here's some interesting factoids I've pulled out so far:

* The only people to mark "Private" as their income had at least a bachelor's degree.

* Out of the responders, the average income for people with a High School education was 58,967.73, some college was 70518.36, and a bachelor's degree was 72603.26 (Note that I removed anyone who marked >1 million as their income, since it skewed things massively).

* The median incomes were HS: 50,000, Some College: 55,000, Bachelor's: 65,000.

I also noticed that several people marked that they made $0 this year, but were not unemployed or students. Would anyone mind clarifying that one?

Good stuff! I think the employed, no income might be startup types who aren't paying themselves (just a guess).

Your assumption is correct (at least for me).

I didn't do the survey. If I had, I would have said I was "employed" as I'm working on two startups. But have income of zero.

I marked self-employed and $0 because I'm working full-time on my own stuff and have no income. I'm living off of savings. (I actually considered putting -$6000, but decided that would be too weird :)

There were a few people who put a negative number, but the only one I saw when glancing through only put -1 (I would assume that was another joke number).

There are 5 -$1's and a -$15,000, from self-employed, student, or small business mostly. More interesting to me are the number of people (211) making $0<$5,000, reported mostly as unemployed or student. I wonder what the breakdown is among unemployed. How many are discouraged, actively seeking, or even retired?

Are these differences statistically significant (according to the data) ?

Who are the 5 that have 10+ in their family?

Perhaps it's the fact that I have to use IE to view certain sites from work (had to vote Corporation), but the age, avg. hours, years in industry, and pre-tax income results are not showing the horizontal bar charts like the other question results.

Very interesting to see the data results, thanks!

This is due to how Google allows you to collect data. Those fields were 'open' so Google doesn't know it can show them in any way other than a list.

That's probably why a .csv is available for download.

Yeah, just downloaded it.

There is a lot of fake data, or I am doing something really wrong.

If you are one of the respondents that makes $680M a year, please contact me...

I took a real quick look to get the data ready for my algorithm and I deleted less than 50 'fake' samples. YMMV

Amazing how there are five 22-year-olds that make $1,000,000

61% Single!

Horrible. I'd recommend getting a life.

Reply on news.ycombinator.com