14. Chivers, C., Leung, B., Yan, N. D. (2014), Validation and calibration of probabilistic predictions
in ecology. Methods in Ecology and Evolution, 5: 1023–1032. doi: 10.1111/2041-210X.12238
23. What if we were to see a surge in patients in a given unit, how would
this propagate to the rest of the hospital?
24. sim·u·di·dactic adj.*
/ˈsimyəˌdīdakt/
To understand by creating a representation
or model of real-world phenomena.
Particularly, using randomization and
computation to understand complex systems
and processes.
C2013: From Latin simulre, simult-, from similis, like and Greek
didaktos, taught;
* I totally just made this up,
but it could be a thing.
25. sim·u·di·dactic adj.*
/ˈsimyəˌdīdakt/
To understand by creating a representation
or model of real-world phenomena.
Particularly, using in randomization and
computation to understand complex systems
and processes.
C2013: From Latin simulre, simult-, from similis, like and Greek
didaktos, taught;
26. Data Science
Seeking Software Engineers (Sr. & mid-level) to help us build out
our real-time predictive application platform
http://www.med.upenn.edu/predictivehealthcare/
• Develop data products and predictive applications
• Collaborate with top medical professionals
• Revolutionize Health care delivery
Contact:
corey.chivers@uphs.upenn.edu @cjbayesian
Editor's Notes
A statistic is a quantity calculable from an observation or set of observations. The Z score is one. Chi-squared, etc. If you can simulate from your null hypothesis, you can build an empirical distribution. If your observation is in the tail, hey presto, you can reject Ho (if you go in for that kind of thing).