A common dream of most baseball aficionados is to visit every ballpark, stepping inside with their own two feet, feeling the history, and seeing every team live. I’m no different; and can already cross off almost two-thirds of the current ballparks off my list (I’m coming for you soon East Coast). After seeing this article on an itinerary that would allow travelers to see every single national park in the 48 contiguous states on a road trip without wasting any time, I wondered how this methodology worked, and how it could be applied to a ballpark journey. As a side note, Randy Olson has also organized the ultimate US road trip and the best cross-Canada journey. I highly recommend him as a follow on Twitter as well!
For those of you that have followed my blog in the past year and a half, one statistical technique that you may have noticed I commonly use is Monte Carlo simulation. While I usually skim over the basics of Monte Carlo simulation to get to the meat of my analysis, I want to take the time in this post to delve into this method a little more deeply, and show by example, the immense power of the Monte Carlo method.
Monte Carlo simulation is a type of probability simulation used by companies to understand the impact of risk and uncertainty in financial, project management, cost, and other forecasting models. It is also a major strategy in decision analytics. One of the drawbacks with trying to predict the future is that you can't know with certainty what the actual value will be...