cle with a particular defect in its emission control system is taken to a succession of randomly selected mechanics until r = 16 of them have correctly diagnosed the problem. Suppose that this requires diagnoses by 20 different mechanics (so there were 4 incorrect diagnoses). Let p = P(correct diagnosis), so p is the proportion of all mechanics who would correctly diagnose the problem. What is the mle of p? p̂ = Is it the same as the mle if a random sample of 20 mechanics results in 16 correct diagnoses? Explain. No, the formula for the first one is (number of failures)/(number of trials) and the formula for the second one is (number of successes)/(number of failures). No, the formula for the first one is (number of failures)/(number of trials) and the formula for the second one is (number of successes)/(number of trials). Yes, both mles are equal to the fraction (number of successes)/(number of failures). No, the formula for the first one is (number of successes)/(number of failures) and the formula for the second one is (number of failures)/(number of trials).
cle with a particular defect in its emission control system is taken to a succession of randomly selected mechanics until r = 16 of them have correctly diagnosed the problem. Suppose that this requires diagnoses by 20 different mechanics (so there were 4 incorrect diagnoses). Let p = P(correct diagnosis), so p is the proportion of all mechanics who would correctly diagnose the problem. What is the mle of p? p̂ = Is it the same as the mle if a random sample of 20 mechanics results in 16 correct diagnoses? Explain. No, the formula for the first one is (number of failures)/(number of trials) and the formula for the second one is (number of successes)/(number of failures). No, the formula for the first one is (number of failures)/(number of trials) and the formula for the second one is (number of successes)/(number of trials). Yes, both mles are equal to the fraction (number of successes)/(number of failures). No, the formula for the first one is (number of successes)/(number of failures) and the formula for the second one is (number of failures)/(number of trials).
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.1: Measures Of Center
Problem 9PPS
Related questions
Question
A vehicle with a particular defect in its emission control system is taken to a succession of randomly selected mechanics until
r = 16 of them have correctly diagnosed the problem. Suppose that this requires diagnoses by 20 different mechanics (so there were 4 incorrect diagnoses). Let p = P(correct diagnosis), so p is the proportion of all mechanics who would correctly diagnose the problem. What is the mle of p?
p̂ =
Is it the same as the mle if a random sample of 20 mechanics results in 16 correct diagnoses? Explain.
No, the formula for the first one is (number of failures)/(number of trials) and the formula for the second one is (number of successes)/(number of failures).
No, the formula for the first one is (number of failures)/(number of trials) and the formula for the second one is (number of successes)/(number of trials).
Yes, both mles are equal to the fraction (number of successes)/(number of failures).
No, the formula for the first one is (number of successes)/(number of failures) and the formula for the second one is (number of failures)/(number of trials).
Yes, both mles are equal to the fraction (number of successes)/(number of trials).
How does the mle compare to the estimate resulting from the use of the unbiased estimator
p̂ =
?
r − 1 |
r + x − 1 |
The mle is greater than the the unbiased estimator.
The mle is less than the the unbiased estimator.
The mle is equal to the the unbiased estimator.
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