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Probabilities with Public Transport

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Shuttles arrive every 5 minutes to take people to the parking lot, the amount of time that passengers wait is uniform continuous probability distribution between 0 and 5 minutes.

How do I draw a graph of this probability distribution of the waiting times using both scales?

What is the probability that the next passenger will wait more than three minutes?

What is the probability that the next passenger will wait between one and a half and four minutes?

What is the expected value for the distribution?

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Solution Summary

Word attachment provides instruction on how to graph waiting times and decide the probability of passenger wait times.

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Shuttles arrive every 5 minutes to take people to the parking lot, the amount of time that passengers wait is uniform continuous probability distribution between 0 and 5 minutes. ...

Solution provided by:
Changping Wang, MA
Education
  • BSc , Wuhan Univ. China
  • MA, Shandong Univ.
Recent Feedback
  • "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
  • "excellent work"
  • "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
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