The manufacturer tests 60 such tires to determine their durability. Assume the life of these tires in miles is 2. A specially designed car tire has an average life of 38,500 miles with a standard deviation of 2,500 miles.A aadig ore type a The manufacturer tests 60 such tires to determine their durability. Assume the life of these tires ln mne approximately normally distributed. (a) Let X = number of miles of a single tire. Find the probability that in the sample above the mean will be less than 38,000 miles. (Use 4 decimals) rox< 38000) =nomolcor (IEa, 3800, 38,500, 2,500)=.5442 born
The manufacturer tests 60 such tires to determine their durability. Assume the life of these tires in miles is 2. A specially designed car tire has an average life of 38,500 miles with a standard deviation of 2,500 miles.A aadig ore type a The manufacturer tests 60 such tires to determine their durability. Assume the life of these tires ln mne approximately normally distributed. (a) Let X = number of miles of a single tire. Find the probability that in the sample above the mean will be less than 38,000 miles. (Use 4 decimals) rox< 38000) =nomolcor (IEa, 3800, 38,500, 2,500)=.5442 born
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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Problem 1P
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Transcribed Image Text:2. A specially designed car tire has an average life of 38,500 miles with a standard deviation of 2,500 ms is
approximately normally distributed.
(a) Let X = number of miles of a single tire. Find the probability that in the sample above the mean will be
less than 38,000 miles. (Use 4 decimals)
rox< 38000) =nomacr (IEa, 3,0o, 38,500, 2,50).5442
PCX
bobnpt.ou vnio
(b) Use the software tool below (or any other) to graph and shade the probability from part (a).
Do not graph manually. The graph should show the appropriate area from part (a).
Tool link: https://mathcracker.com/normal-probability-calculator-sampling-distributions
(c) The tire manufacturer wants to set the tire warranty to 39,100 miles. Is this a good decision? What are
the possible consequences to the manufacturer? Explain in detail.
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