Monte Carlo simulation needs thousands or millions of repeated random draws because a single random pick is not enough. Repeating the random selection many times and storing all the selected values allows us to use those stored results to approximately estimate the distribution around the time to complete both reports.
Conditions: The random selection process is repeated many times.; The selected values are stored.
Monte Carlo simulation needs thousands or millions of repeated random draws because a single random pick is not enough. Repeating the random selection many times and storing all the selected values allows us to use those stored results to approximately estimate the distribution around the time to complete both reports.
Conditions: The random selection process is repeated many times.; The selected values are stored.
The video defines the uniform distribution as a probability distribution that assumes the relative likelihood of all outcomes between a defined minimum and a defined maximum are the same.
Conditions: There must be a defined minimum and maximum.; All outcomes between those bounds are treated as equally likely.
The video defines the uniform distribution as a probability distribution that assumes the relative likelihood of all outcomes between a defined minimum and a defined maximum are the same.
Conditions: There must be a defined minimum and maximum.; All outcomes between those bounds are treated as equally likely.