Work-related accidents at a construction site tend to have a Poisson distribution with an average of 1.5 accidents per week.(a) What is the probability that there will be no work-related accidents at this site during a given week? (Round your answer to three decimal places.)0.223(b) What is the probability that there will be at least 1 work-related accident during a given week? (Round your answer to three decimal places.)0.777(c) What is the distribution of x, the number of work-related accidents at this site per month? (Assume there are four weeks in a month.)p(x) =(d) What is the probability that there will be no work-related accidents during a given month? (Assume there are four weeks in a month. Round your answer to three decimal places.)0.0025

From the information, given thatLet X denotes the number of work related accidents at this site per…

Answered: Work-related accidents at a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A reference states that average daily high temperature in June in a particular city is 86°F with a standard deviation of 7, and it can be assumed that they to follow a normal distribution. We use the following equation to convert "F (Fahrenheit) to "C(Celsius) C-(F-32)=² (a) Write the probability model for the distribution of temperature in C in June in this city. (Round your standard deviation to four decimal places) ~~-[ (b) What is the probability of observing a 31°C (which roughly corresponds to 87.) temperature or higher a a randemily selected day in June in this city? Calculate using the "C model from part (a). (Round your answer to four decimal places.) (c) The probability of observing a 67.8°F temperature or higher on a randomly selected day in June this city is approximately 0.3983, Did you get the same answer or a different answer in part (b)? Are you surprised? Explain. Both sets of calculations produced approximately the same answer which isn't surprising since once we…
4
Tire pressure monitoring systems (TPMS) warn the driver when the tire pressure of the vehicle is 26% below the target pressure. Suppose the target tire pressure of a certain car is 29 psi (pounds per square inch.) (a) At what psi ill the TPMS trigger a warning for this car? (Round your answer to 2 decimal place.) When the tire pressure is (Click to select) v psi. (b) Suppose tire pressure is a normally distributed random variable with a standard deviation equal to 2 psi. If the car's average tire pressure is on target, what is the probability that the TPMS will trigger a warning? (Round your answer to 4 decimal places.) Probability (c) The manufacturer's recommended correct inflation range is 27 psi to 31 psi. Assume the tires' average psi is on target. If a tire on the car is inspected at random, what is the probability that the tire's inflation is within the recommended range? (Round your intermediate calculations and final answer to 4 decimal places.) Probability
Please help me solve this statistics problem from my lecture. Thank you.
The probability that a car will have a flat tire while driving through a certain tunnel is 0.00005. Use the Poisson distribution to approximate the probability that among 14,000 cars passing through this tunnel, exactly two will have a flat tire. Round your answer to four decimal places. OA. 0.1947 B. 0.1703 OC. 0.1217 OD. 0.8783 OE. 0.1460
A professor knows that her statistics students' final exam scores have a mean of 80 and a standard deviation of 12.2. In her class, an "A" is any exam score of 90 or higher. This quarter she has 25 students in her class. What is the probability that 7 students or more will score an "A" on the final exam?Hint: You will need to use your knowledge of normal probability distributions to determine the probability of one individual getting an A and then use your knowledge of binomial distributions to determine the probability of 7 students or more out of 25 students getting an A.prob = ____________Report your final answer accurate to 4 decimal places. Do not round any of the numbers in this calculation until the very end of the problem!
Discuss the connection between the Poisson and exponential distributions.
An IPHONE has an advertised failure rate of 0.01 per hour. The failure rate is constant and the exponential distribution applies. (a) What is the mean time to failure? (b) What is the probability that 300 hours will pass before a failure is observed? (a) The mean time to failure is hours. (Type an integer or a decimal. Do not round.) (b) The probability that 300 hours will pass before a failure is observed is (Round to four decimal places as needed.)
A university is considering setting up an information desk manned by one employee. Based on information obtained from similar information desks, it is believed that people will arrive at the desk at the rate of 18 per hour. It takes an average of 2 minutes to answer a question. It is assumed that arrivals are Poisson and answer times are exponentially distributed. What is the arrival rate? (Include the units.) What is the service rate? (Include the units.) Find the probability that the employee is idle.
Data collected at an airport suggests that an exponential distribution with mean value 2.435 hours is a good model for rainfall duration. (a) What is the probability that the duration of a particular rainfall event at this location is at least 2 hours? At most 3 hours? Between 2 and 3 hours? (Round your answers to four decimal places.) at least 2 hours at most 3 hours between 2 and 3 hours (b) What is the probability that rainfall duration exceeds the mean value by more than 3 standard deviations? (Round your answer to four decimal places.) What is the probability that it is less than the mean value by more than one standard deviation?
Benford's Law claims that numbers chosen from very large data files tend to have "1" as the first nonzero digit disproportionately often. In fact, research has shown that if you randomly draw a number from a very large data file, the probability of getting a number with "1" as the leading digit is about 0.301. Suppose you are an auditor for a very large corporation. The revenue report involves millions of numbers in a large computer file. Let us say you took a random sample of n = 250 numerical entries from the file and r = 60 of the entries had a first nonzero digit of 1. Let p represent the population proportion of all numbers in the corporate file that have a first nonzero digit of 1. Test the claim that p is less than 0.301 by using α = 0.01. What does the area of the sampling distribution corresponding to your P-value look like? a. The area in the right tail of the standard normal curve. b. The area not including the right tail of the standard normal curve.…
(c) Does this Poisson distribution provide a good model for the number of accidents in this example (as per Table 1)? Explain why or why not. Use R to produce a graph to help support your answer (produce the R as part of your answer). (d) Use the model in (b) to estimate the probability that less than 2 accidents were recorded in any randomly chosen week. How does this compare to the actual data?

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