I can explain and apply both curve fitting and error propagation procedures. (chapter 24)
blog post of mine about the Monte Carlo method
editscreencast showing the calculus of error propagation
$$\sigma_f=\sqrt{\left(\frac{\partial f}{\partial a}\sigma_a\right)^2+\left(\frac{\partial f}{\partial b}\sigma_b\right)^2}$$
editsection 20.5 on page 872 does the calculus needed for the maximum probability approach
editscreencast on the Montecarlo theory and implementation in google sheets
screencast on how to do Montecarlo in Mathematica
editWe talked a bit about how to communicate outside of class. For now we're planning to continue the synchronous meetings at 8pm on Sun/Tue/Thurs though Jazz band will have to change that at some point.
For asynchronous we voted on Group Me and now everyone is registered.
We talked about the mean, median, and standard deviation for a triangular distribution (mostly to connect to the concept of expectation value).
They voted on spending some time on the mass/spring system problem. We talked about speed->time->probability and did a bunch of the calculations.
We also spent a little time on the birthday problem, which led to a discussion of when to memorize certain probability formulas (mostly: never).