Discussion Question 1
The exponential distribution also known as the negative exponential distribution describes the period between events. Here is one example:
An example would be to determining how much time will go by before a volcano erupts or how long before a call center will receive its next call. You give a certain time interval of 0-1 and try to determine the length between. The waiting time would be your random variable. The exponential distribution is related to the Poisson distribution.
How about another real world example/ A practical use in the business world?
Discussion Question 2
See if you can explain Bayes' Theorem in your own language.
First of all, what does P(H) mean?
How about the other P's?
What, in plain English, does this equation say?
What can it be used for?
Discussion Question 3
According to figures released by the New York City government, smoking among New York City teenagers is on a decline, continuing a trend that began more than a decade ago (The New York Times, January 2, 2008). According to the New York City Youth Risk Behavior Survey, the teenage smoking rate dropped to 8.5% in 2007 from about 17.6% in 2001 and 23% in 1997. City officials attribute the lower smoking rate to factors including a cigarette tax increase, a ban on workplace smoking, and television and subway ads that graphically depict tobacco-related illnesses. In a report, use the above information to
1. Calculate the probability that at least one in a group of 10 New York City teenagers smoked in 2007.
2. Calculate the probability that at least one in a group of 10 New York City teenagers smoked in 2001.
3. Calculate the probability that at least one in a group of 10 New York City teenagers smoked in 1997.
Identify the smoking trend from 1997-2007.
Explain whether this is a discrete, continuous, or conditional probability.
Explain how probabilities help you understand trends in data.
Recommend steps related to smoking behavior based on this trend.