Listeing to Taleb and Kaplan this morning. Interesting that the someone who teaches you Science does not do Science which could be crucial.
Kaplan emphasises the need for a measure which is why he tries to promote the actually doing of things. His notion of betting can be seen in this way, formalise your thinking and then we can verify it empirically.
Going to start writing ‘results’ section of dissertation to unpack some of the things I’m struggling with.
I started to read ‘On Number Numbness’ from Hofstadter. I like the idea of ‘caching’ reference examples for different orders of magnitude in your head.
Research
Lets orientate around one unit process. Can incorporate all the thinking into this one focus and use it as a template for the others.
Also, worth noting that characterization factor uncertainty also exists.
”Using fuzzy numbers to propagate uncertainty in matrix-based LCI” Tan 2008 Could be useful with ‘expert evaluation’
What if I was literally write a first draft of my dissertation this weekend?
Reading: JC Helton on uncertainty analysis
Reading a bit of Feller. Probability has use in the ‘consequences of assumptions we make’
The no. of possible card distributions in bridge is 2^30. It would take billions of years of everyone on the planet playing day and night to run the experiment on the frequency of receiving a certain card.
However, consequences of the assumption can be verified experimentally, for example, by observing the freqeuencey of multiple aces in the hands at bridge.
It’s more important then when the model doesn’t apply, we know why.