Math Problem Statement
Get final answer for each oart
Solution
Let's go through each part of this problem step by step. This is based on a Poisson process, and the exponential distribution will be key in solving each part.
Given:
- The mean number of customers entering a store every 10 minutes is customers.
- We are using the exponential distribution, which has the probability density function (PDF):
where is the rate (in this case, number of customers per minute).
Since 5.7 customers enter the store every 10 minutes, the rate per minute is:
Now, let's solve each part.
(a) How many minutes can you expect to pass between successive customers entering the store?
The expected value (mean) of an exponential distribution is given by: Substituting :
(b) Compute the probability that at most 2.5 minutes will pass between the arrival of one customer and the next.
For an exponential distribution, the cumulative distribution function (CDF) is: Substitute and : So, the probability is approximately .
(c) Find the probability that at least 1 to at most 3 minutes pass between the entry of two customers.
This is the probability , which is: First, find : Now, find : So, the probability is: Thus, the probability is approximately .
(d) What is the probability that at least 4 minutes will pass until the next customer enters the store, given that at least 1 minute has passed?
This is a conditional probability problem. We need to find: Using the memoryless property of the exponential distribution, this simplifies to: And is: So, the probability is approximately .
Summary of Final Answers:
- (a): minutes
- (b):
- (c):
- (d):
Would you like further details or clarifications on any of these parts? Here are some related questions:
- What is the relation between Poisson and exponential distributions in this context?
- How does the memoryless property of exponential distribution apply to part (d)?
- Can you explain the process to find expected values in an exponential distribution?
- How would the answers change if the rate were different?
- What is the intuition behind the exponential distribution's CDF?
Tip: For exponential distributions, the mean is the inverse of the rate , and it models the time between events (like customer arrivals).
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Math Problem Analysis
Mathematical Concepts
Poisson Process
Exponential Distribution
Probability Theory
Formulas
E(X) = 1 / λ
P(X ≤ x) = 1 - e^(-λx)
P(a ≤ X ≤ b) = P(X ≤ b) - P(X ≤ a)
Theorems
Poisson Distribution
Exponential Distribution CDF
Memoryless Property
Suitable Grade Level
College-level (Statistics)
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