Many business activities generate data that can be thought of as random. For example, a
service
manager
at an auto shop needs to understand the data for cars coming in for services like oil changes. A
variable of interest is the amount of time necessary to service the car, since service time will vary with
each car. They can often capture the most relevant characteristics with a simple probability distribution
model. The service manager can then analyze the model to make predictions and drive decisions, such as
how many technicians to schedule to service demand on a Saturday afternoon.
Respond to the following:
How would you differentiate a discrete from a continuous random variable? Provide a specific
example to illustrate the difference.
Provide a scenario when you use might use one type of random sampling method in your
industry. Explain why you would choose this method in this scenario, even if another random
sampling method could be used?
INTERNAL
USE
