random walks and more about data visualization the drunkard' walk biased random walks treacherous fields monte carlo simulation pascal' problem pass or don' pass using table lookup to improve performance finding some closing remarks about simulation models understanding experimental data the behavior of springs using linear regression to find fit the behavior of projectiles coefficient of determination using computational model fitting exponentially distributed data when theory is missing liesdamned liesand statistics garbage in garbage out (gigo pictures can be deceiving cum hoc ergo propter hoc statistical measures don' tell the whole story sampling bias context matters beware of extrapolation the texas sharpshooter fallacy percentages can confuse just beware knapsack and graph optimization problems knapsack problems greedy algorithms an optimal solution to the / knapsack problem