Finding Probabilities Use the probability distribution you made in Exercise 19 to find the probability of randomly selecting a household that has (c) from one to three HD televisions,
Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 53m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample2h 19m
- 10. Hypothesis Testing for Two Samples3h 22m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
5. Binomial Distribution & Discrete Random Variables
Binomial Distribution
Problem 4.T.7c
Textbook Question
In Exercises 1–7, consider a grocery store that can process a total of four customers at its checkout counters each minute.
The mean number of arrivals per minute is four. Find the probability that
c. one customer is waiting in line after one minute and no customers are waiting in line after the second minute..

1
Step 1: Recognize that this problem involves a Poisson process, as the mean number of arrivals per minute is given (λ = 4), and we are dealing with the probability of a specific number of arrivals in a fixed time interval.
Step 2: Use the Poisson probability formula: P(X = k) = (λ^k * e^(-λ)) / k!, where λ is the mean number of arrivals per minute, k is the number of arrivals, and e is the base of the natural logarithm.
Step 3: For the first minute, calculate the probability that one customer is waiting in line. This means there were 5 arrivals (4 processed + 1 waiting). Use the Poisson formula with k = 5 and λ = 4.
Step 4: For the second minute, calculate the probability that no customers are waiting in line. This means the number of arrivals equals the number of customers processed (4). Use the Poisson formula with k = 4 and λ = 4.
Step 5: Multiply the probabilities from Step 3 and Step 4 to find the joint probability that one customer is waiting after the first minute and no customers are waiting after the second minute.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Poisson Distribution
The Poisson distribution is a probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space, given a known average rate of occurrence. It is particularly useful for modeling the number of arrivals in a queue, such as customers at a grocery store, where events occur independently.
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Queueing Theory
Queueing theory is the mathematical study of waiting lines or queues. It helps analyze the behavior of queues in terms of arrival rates, service rates, and the number of servers. In this context, it can be used to determine the likelihood of a certain number of customers waiting in line at a grocery store checkout.
Probability Calculation
Probability calculation involves determining the likelihood of a specific event occurring, often expressed as a number between 0 and 1. In this scenario, it requires calculating the probabilities of having one customer waiting after one minute and no customers waiting after the second minute, using the Poisson distribution and the principles of queueing theory.
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