Showing posts with label happiness. Show all posts
Showing posts with label happiness. Show all posts

How much are professors paid?

4 comments:
The Washington State employee salary archive that I featured in my last post is a fascinating dataset to explore... including 432k entries for more than 244k people (actually unique names, so likely many more!). There is much you could do with this data, e.g. exploring gender distributions, infer the age distribution by matching the names to the US "Baby Names" data, comparing salaries for similar jobs around the state...

Last time we were looking at salaries for people with the job I have, and comparing them to expectations one might reasonably infer from reading the University's HR website.

Today I'm going to look at the job (notionally) I want: University Professor.

There are 5 publicly funded universities in Washington State. Here is how the 2017 salaries for people whose job contains the word "Professor" compare:
There's a lot to unpack in this graph, even with just 5 curves...
  1. UW is the clear "winner", with a median salary (vertical bar) far above any of its "peers"
  2. UW has a TON of faculty (and/or their faculty have more line-items in the budget - i.e. a single Prof having multiple entries)
  3. The 4 other schools are quite closely clustered around $80k-ish
  4. The 3 schools located east of the Cascade mountains (i.e Eastern, Central, and Washington State) all have very similar primary colors listed on their websites. Coincidentally, these schools all reside in "red" districts. This color proximity drove several design choices for the viz.

But comparing average salaries does not tell the whole story...

These schools are located in vastly different regions of our state: a major city, a rural farming community, a ground transportation hub, an international boarder... and life in each of these cities/towns is equally unique. So for your consideration, here is the same data as above, but normalized by the median home price for each city:
Wow

  1. Given the (ridiculous) cost of living in Seattle, it is no wonder so many faculty now have to live outside the city. For example, I live ~12 miles north of Seattle where home prices are ~27% cheaper.
  2. Bellingham has gotten expensive!
  3. Faculty in eastern Washington are doing substantially better than their western counterparts...  probably much closer to what being a Professor in most cities used to be like (i.e. buying a reasonable house near the University on a faculty salary)
This is an age-old debate when considering the job market for faculty... should one chase the cosmopolitan lifestyle of a big city, or be in the upper echelon of a small town? Clearly you shouldn't just look at top-line salary when considering which university to work at. While there's no "right" answer, I for one find the high earning power of rural faculty quite promising. Small towns can be wonderful places to live, and competitive salaries can bring top talent to these schools. 



One more thing...

Washington state has 30 public colleges (mostly community colleges). Here is the data for jobs listed as "Professor" or "Faculty", with medians shown as heavy circles....
Most of these curves are very skewed towards low salaries, endemic of the state of college faculty hiring and the reliance on part-time labor...


Of course, all the Python code to do this analysis (mostly just bread/butter Pandas) and make these figures (matplotlib) is available on my GitHub profile.

Better Living Through Data

11 comments:
One running theme on this blog has been that of data-driven self study. A favorite source for data about myself is my laptop battery logs. Last summer I shared what an entire year of laptop battery usage looks like, in remarkable detail. Today I'm excited to show the follow up data!

Here is what two years of laptop battery use looks like, sampled every minute I've used my computer(s). This includes 293,952 data points, at time of writing. Since the "batlog" script runs every minute, that translates to over 204 days of computer use in the last ~2 years! Yowza

Update: Per several requests, I have added a more detailed install guide in the README file on github. 
This newer 2013 MacBook Air is holding up much better than the 2012 model, and I'm consistently still getting 6-8 hours of life out of the battery at least. The scatter on the battery capacity for the 2013 model is higher, which is mildly interesting. For reference, Time = 0 for the older model (blue) occurred at Tue Aug 14 10:41:46 PDT 2012, and for the newer model (red) at Sat Aug 24 12:16:00 PDT 2013.

Quantifying Happiness?

6 comments:
Over the holidays I spent a weekend vacationing in San Francisco with my lovely wife. We had a great time eating and drinking our way around the City by the Bay. I brought back a wonderful souvenir: a tin of excellent coffee beans from one of the many cafes I wandered in to that weekend.

I truly enjoyed the coffee, the simple presentation of the beans in the tin, and the memories of the great breakfast we had at their cafe. (Food/drink is always my favorite souvenir). I enjoyed it so much, I made this silly "graph" charting my happiness as I opened and sampled the coffee a few days before Xmas.
This raised a question in my mind that I invite you, dear reader, to comment on!
Can we really quantify happiness?

In other words, could we actually measure the enjoyment of something as simple as a cup of coffee in real time?


I know research has been done on quantifying pain, and the state of happiness does release lots of unique chemicals into the brain. But happiness is a complex and often subtle emotion. In what way does elation differ from stoic satisfaction?

Of course, I'm not the only one considering such questions. Given how important happiness (and its many variants) is to quality of life, health, stress, and consumerism, I'd imagine it's an important area of research.

It is also a topic of frequent pseudo-charts, like mine above. Here are a few from PhD comics to amuse: Work output vs time, Vacation vs stress, Motivation level vs time. My first officemate in gradschool also once drew "Happiness vs Time in Gradschool". It was an illuminating, albeit somewhat depressing, visualization.

I invite your thoughts, links to relevant literature, or links to other good pseudo-charts on the subject in the comments below