Twenty motors were put on test under a high-temperature setting. The lifetimes in hours of the motors under these conditions are
given below. Suppose we assume that the lifetime of a randomly selected motor under these conditions, X, has a Gamma (1, theta) distribution.
(a) Derive the maximum likelihood estimate of 9 and evaluate it numerically.
(b) Obtain the sample median of the data, which is an estimate of the median lifetime of a motor. What parameter is it estimating (i.e., determine the median of X)?
(c) Based on the mle, what is another estimate of the median of X?
(d) Obtain a large sample approximate 95% confidence interval for the mean lifetime of a motor.
(a) Derive the maximum likelihood estimate of 9 and evaluate it numerically.
(b) Obtain the sample median of the data, which is an estimate of the median lifetime of a motor. What parameter is it estimating (i.e., determine the median of X)?
(c) Based on the mle, what is another estimate of the median of X?
(d) Obtain a large sample approximate 95% confidence interval for the mean lifetime of a motor.
1 answer:
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P(
successes in 
trials) = ⁿ
×![[P(Success)^{r}]](https://tex.z-dn.net/?f=%20%5BP%28Success%29%5E%7Br%7D%5D%20)
×![[P(failure)]^{n-r}](https://tex.z-dn.net/?f=%20%5BP%28failure%29%5D%5E%7Bn-r%7D%20)
We have
Substitute these values into the formula, we have
P( 2 success in 8 trials) = ⁸C₂ × (0.15)² × (0.85)⁶
P( 2 success in 8 trials) = 0.2376.... ≈ 0.24 = 24%
We have
Substitute these values into the formula, we have
P( 2 success in 8 trials) = ⁸C₂ × (0.15)² × (0.85)⁶
P( 2 success in 8 trials) = 0.2376.... ≈ 0.24 = 24%