NSERC Discovery Grants 2012 in Computer Science
The day of the publication of the results of the NSERC Discovery Grants for 2013 is approaching, and I just realized that I didn’t publish the ones from 2012, which I did for 2011.
What is the distribution of grants?
First, the total amount for Discovery Grants in Computer Science was $5,943,920 per year ($5,126,543 last year) divided into 227 grants (202 last year). There were 11 1-year, 3 3-year, 213 5-year (10 1-year, 1 2-year, 1-3 year and the rest 5 years in 2011). They went to 49 different institutions (45 in 2011).
Minimum amount was (like the year before) $14k, first quantile $17k (20k last year), median $22k (24 last year), average $26,185 ($25.380k last year), third quartile $28k ($29k), and maximum of $122.2 ($96k last year). A Shapiro-Wilk test shows that this distribution appears NOT to be normal (p << 0.01).
Compared to 2011, there was more money available per person (26.2k versus 25.4k), and there were many more smaller grant, but also the larger grants accounted for a larger share (one person got a lot of money).
This is the distribution of grants per amount.
A simple way to visualize this data is tot plot individuals to amounts. Colours reflect the province (click to enlarge):
As it can be seen, there is a fairly uniform distribution across the lowest amounts, with few outliers to the right. Not surprisingly Ontario is, again, the most frequent. Ontario and BC represent most of the points at the right side.
Here is a breakdown of the 4 big ones:
How do institutions compare?
I present the results arranged by University. Each vertical column is a university; they have been sorted by province. Each point in the plot is a recipient. The colour of the point represents the type of grant (1 to 5 years). Most are 5 years, with few being 1 year (what I call probation grant: they either have faith you can do significantly better next year, or they are giving you a warning signal).
The median across the country was $22k per year (in the spirit of disclosure mine is $24k–2011).
The boxplots are a simpler way to compare universities and are overlayed on the data. I have removed outliers from them to avoid confusion with the data points. Of course, if you have paid attention to your stats courses you will know that boxplots are good when the data is normally distributed (which I don’t assume it is). Hence their use in this data is flawed, but they are still useful.
I also got curious who the high fliers were. And below the points are labelled.