Become less valuable over time
Po = 0.5385, Lq = 0.0593 boats, Wq = 0.5930 minutes, W = 6.5930 minutes.
<u>Explanation:</u>
The problem is that of Multiple-server Queuing Model.
Number of servers, M = 2.
Arrival rate,
= 6 boats per hour.
Service rate,
= 10 boats per hour.
Probability of zero boats in the system,
= 0.5385
<u>Average number of boats waiting in line for service:</u>
Lq =![[\lambda.\mu.( \lambda / \mu )M / {(M – 1)! (M. \mu – \lambda )2}] x P0](https://tex.z-dn.net/?f=%5B%5Clambda.%5Cmu.%28%20%5Clambda%20%2F%20%5Cmu%20%29M%20%2F%20%7B%28M%20%E2%80%93%201%29%21%20%28M.%20%5Cmu%20%E2%80%93%20%5Clambda%20%292%7D%5D%20x%20P0)
=
= 0.0593 boats.
The average time a boat will spend waiting for service, Wq = 0.0593 divide by 6 = 0.009883 hours = 0.5930 minutes.
The average time a boat will spend at the dock, W = 0.009883 plus (1 divide 10) = 0.109883 hours = 6.5930 minutes.
The purchase of low-quality materials would most likely the result of a favorable materials price variance coupled with an unfavorable material usage variance. Material price variance is the difference between the cost and the budgeted and actual cost to obtain an object or materials, multiply to the total amount of the product purchased. They are what you called positive value of direct material price and negative value of direct material price. A positive value of direct material price variance is the one that is favorable and it means that the direct material was purchased for a lesser price than the standard price. A negative value of direct material price variance is the one that is unfavorable and it means that more than the expected price per unit is paid.
Answer:
3.44%
Explanation:
The computation of the return if sold the fund at the year end is shown below:
= {[Price × (1 - Front End Load) × ((1 + fund increase percentage) -expense ratio)] - price} ÷ price
={[$20 per share × (1 - 5.75%) × ((1 + 11%) - 1.25%)] - 20} ÷ 20
= 3.44%
We simply applied the above formula so that the correct return could come