random walks and more about data vizualization when we executed drunktest(( ) usualdrunk)it printed usualdrunk random walk of steps mean cv max min usualdrunk random walk of steps mean cv max min usualdrunk random walk of steps mean cv max min usualdrunk random walk of steps mean cv max min this is surprisinggiven the intuition we developed earlier that the mean distance should grow with the number of steps it could mean that our intuition is wrongor it could mean that our simulation is buggyor both the first thing to do at this point is to run the simulation on values for which we already think we know the answerand make sure that what the simulation produces matches the expected result let' try walks of zero steps (for which the meanminimum and maximum distances from the origin should all be and one step (for which the meanminimum and maximum distances from the origin should all be when we ran drunktest(( , ) usualdrunk)we got the highly suspect result usualdrunk random walk of steps mean cv max min usualdrunk random walk of steps mean cv max min how on earth can the mean distance of walk of zero steps be over we must have at least one bug in our simulation after some investigationthe problem is clear in simwalksthe call walk(fhomernumtrialsshould have been walk(fhomernumstepsthe moral here is an important onealways bring some skepticism to bear when looking at the results of simulation ask if the results are plausibleand "smoke test" the simulation on parameters for which you have strong intuition about what the results should be in the th centuryit became standard practice for plumbers to test closed systems of pipes for leaks by filling the system with smoke laterelectronic engineers adopted the term to cover the very first test of piece of electronics--turning on the power and looking for smoke still latersoftware developers starting using the term for quick test to see if program did anything useful