Off meal plan (junior year roundup)

Out of 3 months' worth of posts on this blog, the most viewed post (I love the blogger stats feature!!) has been this one on the difference between Brown's meal plan and my being off meal plan. I fond that really interesting, because I thought that some of the other graphs were more interesting (at least, I had more fun making them). But I guess $$$ issues are always going to be taken seriously.

About a week ago meal plan ended - i.e. dining halls closed and everyone was left to fend for themselves. So now I had exact numbers to compare for meal plans vs. feeding myself for an equivalent amount of time. And then I waited around for a week waiting for research plans to be approved, etc - giving me time to graph them. I think this graph is a bit of an improvement over the last because it shows actual values, and puts the numbers in terms of things that are a bit more tangible, especially to students. Also, it has many colours! that I think (and hope) complement the numbers rather than distract.

Some of these things are probably more relevant to me (I bought my ticket to Quito, Ecuador a few weeks ago, and the rent/average grocery expenditure numbers are mine) but I think

Also, this doesn't even touch on what happens when you compare costs of living and focus just on basic needs...I pay $38 a month to feed and educate a little boy in Indonesia, and the $2174 would support him for 57.2 months = almost 5 years. He would be 12 years old before that money ran out.

The General Election, in Facebook-land

Thanks to the General Election I was supremely unproductive yesterday. I am actually not 100% sure what I feel about the results themselves. But there is change in the air that makes it hard not to be excited. And I am optimistic enough to believe that the change will be for the better.

Anyway, there has been a lot said about the role of social media in this election. I was certainly thinking that as I watched the updates roll in on Twitter while Channel News Asia did their millionth 'analysis' of the constituencies and candidates and then started talking about Osama and golf results (!?!). But sometimes the role of social media can be a little...overblown?

I did a brief survey of a bunch of Facebook fan pages this morning, and here is what I found.

(data correct at time of collection, ~10am EDT; almost certainly no longer correct)

So apparently the returning officer who has burned "pursuant to Section 49, Subsection 7E, Paragraph A of the Parliamentary Elections Act" into our brains forever is better liked than the PM. The ranting can start now.

I will add that if you use Facebook likes as an actual measure of things liked, I am like that grumpy old man who hates the world and waves his cane at small children. For the record, I actually like small children, except on planes.

Algae people!

I attended my second scientific conference in five weeks (also my second conference EVER) this weekend: the 50th anniversary symposium of the Northeast Algal Society at Woods Hole. As might be expected from a group that focuses on algae, this was a much smaller, intimate conference than the Benthic Ecology Meeting, and they gave everyone a full list of attendees' names, affiliations and contact information. AKA graphable data. So here we go...

I wanted to look at where people were from, i.e. which institutions sent the most algae people out to Woods Hole. This graph is something similar to a rank abundance curve, with institutions ranked by the number of attendees on the abscissa and the number of attendees on the ordinate (the terms 'abscissa' and 'ordinate' make me happy because though they are so ridiculously obscure). The institutions with the biggest contingents were: University of New Brunswick, UConn, URI, UNH and Northeastern. I was the only one from Brown :)


Here is a plot of how far people were from their home institution. It is based on point to point distance measurements in Google Earth, so it most certainly underestimates the actual distance traveled by each person (especially because Cape Cod is a funny shape).


Woods Hole is awesome and today was sunny so I was very happy. Here is a picture from near the conference building.

Minimum ages

I spent most of today making regression models to analyse nutritional data from the McDonalds menu for my statistics class. It was surprisingly fun.

Unrelatedly, here is a quick graph.


Make of it what you will.

I'm not voting in this year's election because I no longer have an address in Singapore and therefore I no longer have a constituency :(

Graphs of a blog of graphs

It's about time this happened, because there was no way I could let these pretty graphs just sit there. Blogger records visitor stats for the blogs it hosts and graphs them. So there are graphs of this blog's visitor traffic. Fig. 1 is a graph of visitor operating systems.

Fig. 1. Visitor operating systems for this blog

Compare that with the OS composition of another more high-traffic Blogger-hosted blog with stats I can access: the TA-run Brown ecology class blog (Fig. 2). Brown is rather maccy in general, but this is a really big difference!!

Fig. 2. Visitor operating systems for Brown ecology class blog

Finally, a general comparison is in order. As I did before when comparing my class diversity over time, this is basically a H' index. I wonder what Shannon et al. would think of my using their index to quantify diversity in ridiculous things, but it's the most familiar measure of diversity to me and here it is (Fig. 3).

Fig. 3. Diversity of this blog vs. the ecology blog

Of course, my real point in posting all these graphs is this idea: if I blog the graphs of the blog and then graph the blog of the graphs of the blog etc. etc. IT WOULD GO ON FOREVER!!!

Next time: web browser diversity!


As a side note: There is obviously some non-independence going on here (e.g. repeat visitors, of which I am sure there are many many many). But this is Blogger's fault and not mine and I am not making any statistical inferences here, so I'm going to pretend all is fine.

Why "earth hour" annoys me

Because I see no reason to sit in the dark for an hour (other than making yourself feel all fuzzy inside) when there are a million other things you could do to cut energy use more effectively (and without cutting productivity). Like turning off the lights when you're not using them, and not running the hot water when you're not even touching the water, and not taking hour-long hot showers (I am especially bothered by people wasting water because it's like a 2 in 1 'water and energy' going down the drain).


* My room is lit by 2 x 36W fluorescent bulbs in a standing lamp.
** Taking an average shower flow rate of 2.5 gal/min, numbers from here. Note that this is calculated assuming 100% efficiency of the water heater, which is an impossibility, so any realistic value would be higher than what is graphed.

Off meal plan

This is a graph idea that came out of the inevitably frequent conversations with people on my hall and other 'off meal plan' upperclassmen about how ridiculously expensive the college meal plan is. I think it comes out to something like $9 a meal, but a number like that is not that easy to compare to the less well-defined manage-your-own-food-budget. I generally think of meal plan as 'a lot' more expensive than off meal plan but have no clear conception of what 'a lot' is. I decided it would be easier to visualise if I graphed it.

I was pretty surprised at how much 'a lot' really was. My initial idea was to stack things up on my 'off meal plan' bar until it equaled the meal plan bar but I pretty much ran out of 'large expense' things to stack, with over $200 to go.

The graph isn't meant to convey an expenditure switch because none of the other expenses actually 'came out' of meal plan money - Benthics $$ came out of a Brown travel grant and TA stipend, NEAS from the stipend and a research assistant job, dive gear came out of a summer research fellowship, etc. - it's just a visual comparison of magnitude.

Other (qualitative) benefits of not paying the college to make food for you:
1. flexibility
2. feeling like a real person
3. not being utterly lost and helpless when the dining halls close (spring break week, ha.)

Okay I am off to make lunch and work my butt off so I can spend the second half of next spring break freezing in Nahant water and looking for algae.

In and out

I've been scrambling to catch up with everything ever since I got back from the Benthic Ecology Meeting five days ago so I haven't had the time to mess around with data and graphs. But now it's spring break, and even though I have a to-do list as long as my arm, there's some time to play around with excel.

Like most conferences that aren't tiny, Benthics has concurrent sessions (4 of them) and they were close enough that it was very easy to switch from one session to another between talks. Each session had 5-10 talks, so 4-9 potential switches in total. Here is a graph of how much switching we all did (as a proportion of how many possible switches there were):

FYI, we are almost but not 'significantly different' from each other (p~0.09). Though I bet if I just ran a paired test between me and Jason we'd be different. I think I just want to believe that I am significantly different from smelly Jason :)

And below is another graph of switches (again, proportion of total possible), this time by session. Yes, there was one session in which I switched rooms at every possible time, though I think it was mostly moving back and forth between two of the rooms.


Also, 2 great graph ideas that may never see the light of ordinate and abscissa:

1. I wanted to graph our individual paths and movements between sessions, but we moved around and crossed between rooms so much that the graph is just a crazy mess of lines which fails to convey the point. Even the above graph (switching by section) is a little but crazy and falls on the very limit of what I consider worth graphing.

2. If I could figure out which combination of talks each person at Benthics attended, I could use some kind of ordination technique (I'm not sure exactly which would be most suitable) to characterise each person relative to everyone else based on that. Then people who cluster together would probably have similar interests and should talk to each other => awesome way to network, right? But it's kind of lame to do this when I only have data for 4 people. Maybe if I go to Benthics again next year I will try and do this...

Research diving vs. 'fun diving' (Part 2)

Obviously this is because I work in shallow old New England.

The p-value is from a two-sample t-test run in STATA.