The average waiting time per customer at a briskly food restaurant have be 7.5 minutes. The customer waiting tim
The average waiting time per customer at a hasty food restaurant have be 7.5 minutes. The customer waiting time have a average distribution. The executive claims that the use of a unmarked teller system will dwindling the average customer waiting time in the store. A disorganized token of 12 customer transactions have be record. At a significance plane of .05, what is the rejection point condition? We would reject the null hypothesis if
Answers:
If it is really a jumbled preview, you could use a T experiment, the problem is that you will be 95% confident that the average be determined waiting time will be some huge gamut similar to between 3 and 11 minutes. So since your starting average is still inside that capacity, it is really senseless.
I used to work in vigorous food. I worked at Burger King for something like a year. And intensely few cars find out at 7-10 minutes. Each in haste food CORPORATION NOT FRANCHISE. Is committed to making respectively saloon obtain out at going on for 2.5 minutes. Then, after the cars travel through, the time averages and it will show the average time that cars hold be going out and I hold never see it as big as 7.5 the great I ever saw it be give or take a few 5 minutes. Go work at a hurried food restaurant and you'll see the manager drastically concerned something like the timing of drive thru if it is a corporation. If it is a franchise the manager probably won't guardianship as much.
From a statistical perspective in that is not satisfactory information to answer the grill. The assumption you working below is that the banker is the constraint in the process. I own done this type of process recovery up to that time and I hold seldom found that desk clerk is the constraint. And even if it is, the accumulation of a teller simply moves the constraint minus significant impact on the overall cycle time of the process.
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Answers:
If it is really a jumbled preview, you could use a T experiment, the problem is that you will be 95% confident that the average be determined waiting time will be some huge gamut similar to between 3 and 11 minutes. So since your starting average is still inside that capacity, it is really senseless.
I used to work in vigorous food. I worked at Burger King for something like a year. And intensely few cars find out at 7-10 minutes. Each in haste food CORPORATION NOT FRANCHISE. Is committed to making respectively saloon obtain out at going on for 2.5 minutes. Then, after the cars travel through, the time averages and it will show the average time that cars hold be going out and I hold never see it as big as 7.5 the great I ever saw it be give or take a few 5 minutes. Go work at a hurried food restaurant and you'll see the manager drastically concerned something like the timing of drive thru if it is a corporation. If it is a franchise the manager probably won't guardianship as much.
From a statistical perspective in that is not satisfactory information to answer the grill. The assumption you working below is that the banker is the constraint in the process. I own done this type of process recovery up to that time and I hold seldom found that desk clerk is the constraint. And even if it is, the accumulation of a teller simply moves the constraint minus significant impact on the overall cycle time of the process.