Probability Problem (maybe on Negative Binomial Distribution)

In summary, the conversation discusses a problem from the book "Probability and Statistics in Engineering - Hines, Montgomery" about a potential customer entering a car dealership every hour and the probability of a salesperson concluding a transaction. The question asks for the probability of the salesperson having to work exactly 8 hours and more than 8 hours. The solution involves calculating the probability of selling a car at the 8th hour and the probability of selling less than 3 cars in 8 hours. The final answer for the probability of working more than 8 hours is 0.962.
  • #1
Debdut
19
2
The following problem is from "Probability and Statistics in Engineering - Hines, Montgomery"

A potential customer enters an automobile dealership every hour. The probability of a salesperson concluding a transaction is 0.10. She is determined to keep working until she has sold three cars. What is the probability that she will have to work exactly 8 hours? More than 8 hours?

Soln: I have done it. Don't know whether the process is correct. Also I think the answer is low in value. Want to get your opinion.

She will have to work exactly 8 hours means - She will sell the last car at 8th hour and stop working.

The probability of selling a car at 8th hour (any hour) = 0.1. Thus we have got the last hour calculated.
We have the preceding 7 hours. Two cars will be sold at any two of the 7 hours and for remaining 5 hours no car will be sold.
Probability of that = 7C2 . (0.1)2 . (0.9)5 = 0.124
Total Probability = 0.124 . 0.1 (for last hour) = 0.0124

I am trying the 2nd part.
 
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  • #2
OK, here's the 2nd part -

P(working more than 8 hours) = P(selling less than 3 cars in 8 hours)
= P(selling 0 car in 8 hours) + P(selling 1 car in 8 hours) + P(selling 2 cars in 8 hours)
= 8C0 . (0.1)0 . (0.9)8 + 8C1 . (0.1)1 . (0.9)7 + 8C2 . (0.1)2 . (0.9)6
= 0.962
 
  • #3
It all looks right to me.
 

1. What is a probability problem?

A probability problem is a mathematical question that involves determining the likelihood of a certain event or outcome occurring. It typically involves using statistical concepts and formulas to calculate the probability of an event happening.

2. What is the negative binomial distribution?

The negative binomial distribution is a probability distribution used to model the number of successes in a series of independent and identically distributed trials, where the probability of success is constant. It is often used to calculate the probability of obtaining a certain number of failures before a specified number of successes occur.

3. How is the negative binomial distribution different from the binomial distribution?

The negative binomial distribution differs from the binomial distribution in that the binomial distribution calculates the probability of a specific number of successes in a fixed number of trials, whereas the negative binomial distribution calculates the probability of a specific number of trials needed to achieve a certain number of successes.

4. How do you calculate the mean and variance of a negative binomial distribution?

The mean of a negative binomial distribution is equal to r/p, where r is the number of successes and p is the probability of success. The variance is equal to r(1-p)/p^2. These values can be calculated using a calculator or by hand using the appropriate formulas.

5. In what real-life situations can the negative binomial distribution be applied?

The negative binomial distribution can be applied in various real-life situations, such as predicting the number of calls a customer service representative will receive before a certain number of complaints are resolved, calculating the number of attempts it takes to successfully complete a task, and determining the number of trials needed to obtain a certain number of sales in a marketing campaign.

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