Answer:
a.
P(A > 2,659)= 0.5239
P(B > 2,659)= 0.4325
Process A will be investigated more often.
b.
P(A > 2,659) = 0.8186
P(B > 2,659)= 0.6406
Process A will be investigated more often.
d.
K= 5.7741
P(B> 5.77409)= 0.51595
Explanation:
Hello!
The cost variance is defined as the difference between a budget cost and an actual cost.
There are two processes of interest:
Process A: stable: easily controlled production process with little fluctuation invariance.
Process B: random events: the equipment is more sensitive and prone to breakdown, the raw material prices fluctuate more,...
Since he's paying more attention to B, even though both processes have the same probability of developing inefficiency, he decides to investigate each process if their variances exceed $2659 regardless of what the process is.
In control:
Process A
Mean cost variance (in control) $ 3
The standard deviation of cost variance (in control) $5,473
Process B
Mean cost variance (in control) $ 1
The standard deviation of cost variance (in control) $9,743
Out of control
Process A
Mean cost variance (out of control) $7,651
The standard deviation of cost variance (out of control) $5,473
Process B
Mean cost variance (out of control) $ 6,169
The standard deviation of cost variance (out of control) $9,743
a) The cost variances of both processes have a normal distribution, they will be investigated if the cost variance is greater than $2,659, symbolically:
Both are "in control" so you have to use the given data for this characteristic.
P(A > 2,659)
And
P(B > 2,659)
Since both variables have a normal distribution you can calculate these probabilities using the standard normal distribution as:
For process A
P(A > 2,659) = P(Z>
)
P(Z>-0.06)= 1 - P(Z ≤ -0.06) = 1 - 0.47608= 0.52392
For process B
P(B > 2,659)= P(Z>
)
P(Z> 0.17)= 1 - P(Z ≤ 0.17)= 1 - 0.56749= 0.43251
Process A will be investigated more often.
b. For this item you have to calculate the probability that the process are going to be investigated, asuming the cost variances have normal distribution, but the processes are out of control. This means you have to use the values of the second data set.
For process A
P(A > 2,659) = P(Z>
)
P(Z>-0.91)= 1 - P(Z ≤ -0.91) = 1 - 0.18141= 0.81859
For process B
P(B > 2,659)= P(Z>
)
P(Z> -0.36)= 1 - P(Z ≤ -0.36)= 1 - 0.35942= 0.64058
Process A will be investigated more often.
c. Looking at the probabilities of both process "out of control", process A has a grater probability than process B of having a variance cost greater than $2.659. That's why process A will be investigated more often.
d.
In this case, they want to know what is the number of cost variance that leads process B "in control" to have a probability of 0.3121 of being investigated. In this case, you have to do a reverse standardization, this means, you know the probability and need to look for its corresponding value.
P(Z>k)= 0.3121
P(Z>k) = 1 - P(Z ≤ b)
1 - P(Z ≤ k)= 0.3121
P(Z ≤ k)= 1 - 0.3121
P(Z ≤ k)= 0.6879
Now you have to look in the table for the number "b"that corresponds to the cummulative probability of 0.6879,
k= 0.49
Now k=
0.49*9.743= K - 1
4.77409 + 1 = K
K= 5.77409
Process B will be investigated if its cost variance is greater than $5.77409
Using this new policy you need to calculate the probability of B "out of control" to be investigated:
P(B> 5.77409) = P(Z>
)
P(Z> -0.04)= 1 - P(Z ≤ -0.04)= 1 - 0.48405= 0.51595
I hope it helps!