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View Policies Current Attempt in Progress In Applied Life Data Analysis (Wiley, 1982), Wayne Nelson presents the breakdown ti
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Here in this scenario we have to identify whether the given sample is comes from normally distributed population.

To answer this we have to plot the normal probability plot. Normal probability plot is the plot of Standerd normal value against the observation. If we found that the 45° pattern or linear pattern then we can say that the sample is comes from normally distributed population.

To plot the normal probability plot we need following table :

The sample size is n = 19. The following table shows the sample data provided, sorted in ascending order. Also, the theoretical frequencies fi are computed as well as the associated z-scores zi, for i = 1, 2, ..., 19i=1,2,...,19:

Position (i) X (Asc. Order) fi zi
1 0.30 0.0325 -1.846
2 0.84 0.0844 -1.376
3 0.99 0.1364 -1.097
4 1.23 0.1883 -0.884
5 2.74 0.2403 -0.705
6 3.02 0.2922 -0.547
7 4.23 0.3442 -0.401
8 4.71 0.3961 -0.263
9 4.73 0.4481 -0.131
10 6.59 0.5 0
11 7.26 0.5519 0.131
12 7.95 0.6039 0.263
13 8.16 0.6558 0.401
14 12.07 0.7078 0.547
15 31.62 0.7597 0.705
16 32.67 0.8117 0.884
17 33.86 0.8636 1.097
18 36.61 0.9156 1.376
19 73.00 0.9675 1.846

Observe that the theoretical frequencies fi are approximated using the following formula: < fi į – 0.375 n +0.25 where i corr

From the above normal probability plot we can see that the linear pattern which indicates that the sample is in approximately linear trend.

answer,

A) Breakdown times is normally distributed.

Thank you.

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