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Now that
we've built a couple of models to illustrate
the basic concepts, we'll take the next step
of building a model that actually solves a
problem that would be difficult to solve
without a Monte Carlo method approach.
We will
calculate the time it takes to commute from
home to the office. We are trying to
answer the following two questions:
1. How
much time do I need to allow in order to
have 75% confidence that I will arrive on
time?
2. How much time should I allow in
order to have 99.5% confidence that I will
arrive on time (on days that start with an
important meeting)?
Later in this
tutorial we will cover how to model
variables that follow normal distribution
curves. For now, though, we'll keep it
a bit less complex. Our algorithm for
getting to work is as follows:

Drive 2
miles on a highway, with 90% probability
you will be able to average 65 MPH the
whole way, but with a 10% probability
that a traffic jam will result in
average speed of 20 MPH.

Come to
an intersection with a traffic light
that is red for 90 seconds, then green
for 30 seconds.

Travel 2
more miles on a surface street.
70% of the time you travel at 30 MPH.
10% of the time you average 20 MPH, 10%
of the time you average 40 MPH, and 10%
of the time there's a traffic jam that
takes you 30 minutes to travel these two
miles.
On the
next page we'll develop an Excel
equation for each of the three steps of
our commute.
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