[stevegalla]

> I desperately want to get to a point where I'm able to quickly sketch out a statistical model for making a decision

What kind of decisions do you want to make? If you offer that up, others will be able to provide guidance to frameworks used to make those decisions.

The field of operations research uses topics from all sorts of fields to try to make better decisions. I would broadly classify modelling into two large categories deterministic (e.g., how to schedule a flight crew, or where to locate a warehouse) or stochastic (using probability models, e.g., how many people to staff in a bank). Of course there is no problem that will be strictly one form or the other. There will be points in a modelling problem where it's useful to apply tools from both categories.

A decision tree might be the simplest form. You map out the different decision points and can generate costs or profits and probabilities for the decision points. You take the one that has the highest expected value (sum of probability of outcome times value of outcome) of profit or lowest expected value of cost.

Sensitivity analysis may be another tool to use in decision making. You don't need to get three decimal accuracy. Come up with some upper and lower bounds and you'll have an idea of how good or how bad the outcome will be.

Determining the probabilities and bounds may be tough, and your decision will only be as good as the data your putting into the framework.