Question
Consider the time series model
where
(i) Is this a stationary time series?
(ii) What are the mean and variance of the time series?
(iii) Calculate the autocorrelation function.
(iv) Plot the correlogram.
The failure data for 40 electronic components is shown below:
Operating Time (in hours) |
0-5 | 5-10 | 10-15 | 15-20 | 20-25 | 25-30 |
Number of Failures | 5 | 7 | 6 | 4 | 5 | 4 |
Operating Time (in hours) |
30-35 | 35-40 | 40-45 | 45-50 | ≥50 | |
Number of Failures | 4 | 0 | 2 | 1 | 2 |
Estimate the reliability, cumulative failure distribution, failure density and failure rate functions.
Differentiate between the autoregressive and moving average models of time series.
A manufacturer of men’s jeans purchases zippers in lots of 500. The jeans
manufacturer uses single-sample acceptance sampling with a sample size of 10 to
determine whether to accept the lot. The manufacturer uses c = 2 as the acceptance
number. Suppose 3% nonconforming zippers are acceptable to the manufacturer and
8% nonconforming zippers are not acceptable. Find
(i) Probability of accepting a lot of incoming quality 0.04.
(ii) Average outing quality (AOQ), if the rejected lots are screened and all defective
zippers are replaced by non-defectives.
(iii) Average total inspection (ATI).
A manufacturer of men’s jeans purchases zippers in lots of 500. The jeans manufacturer uses single-sample acceptance sampling with a sample size of 10 to determine whether to accept the lot. The manufacturer uses c = 2 as the acceptance number. Suppose 3% nonconforming zippers are acceptable to the manufacturer and 8% nonconforming zippers are not acceptable. Find
(i) Probability of accepting a lot of incoming quality 0.04.
(ii) Average outing quality (AOQ), if the rejected lots are screened and all defective zippers are replaced by non-defectives.
(iii) Average total inspection (ATI).
Consider the time series model
where
(i) Is this a stationary time series?
(ii) What are the mean and variance of the time series?
(iii) Calculate the autocorrelation function.
(iv) Plot the correlogram.
The R- chart is suitable when subgroup size is greater than 10.
Consider the time series model
Where
(i) Is this a stationary time series?
(ii) What are the mean and variance of the time series?
(iii) Calculate the autocorrelation function.
(iv) Plot the correlogram.
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