Twenty-one chapters about the Canadian contribution to statistical theory and practice. I thought I’d try writing pi-ems about each chapter, where the number of words in each line of the poem is 3, 1, 4, 1, 5, 9. To avoid the posts getting too long, I’ll do them in batches of seven. Here’s the third and final instalment!
Chapter 15. Statistics in financial engineering.
Clear Canadian contributions
From Black-Scholes on.
Financial engineers contribute much and
A statistical formula on its own is not dangerous.
Chapter 16. Making personalised recommendations in e-commerce
Loved the writing:
Loved the models too:
Not a specially Canadian issue
But an interesting multivariate problem with websites to boot.
Chapter 17. What do salmon and injection drug users have in common?
Elusiveness, that’s what!
And lots of Canadian research.
Unexpected drops in sockeye populations driving much research effort.
18. Capture-recapture methods for estimating the size of a population: dealing with variable capture probabilities
Animals including mice.
This time illegal immigrants.
With Binomial and Poisson models
And a variety of tools to cope with heterogeneity.
19. Challenges in statistical marine ecology
Counting marine populations:
Hammerhead sharks, Atlantic cod:
Zero-inflated? No, hurdle.
Bycatch data yields knowledge thanks to friends of old.
20. Quantifying the human and natural contributions to observed climate change.
Climate change is
graphs and models reveal.
big data and small sample
come together with distributed modelling and strong assumptions.
21. Data hungry models in a food hungry world: an interdisciplinary challenge bridged by statistics.
Satellite remote sensing
For predicting crop yield.
Indices I’d never heard of.
Nice analytical framework including linear models, forecasting and hindcasting!