What is the confidence interval?

Simulation Modeling and Experimental Design Assignment The Hungarian Greek fusion burritos truck has decided to do a more complete simulation. Arrivals: you estimated customers arrive in a uniform distribution with a minimum of 0 seconds and a maximum of 30 seconds between customers. To simulate a uniform distribution, simply multiply the random number by the range (maximum minus minimum) and add that to the minimum. As you will see next time, this simulates the time between arrivals and we can use this to calculate the actual arrival times. Service: you estimated the service time as an exponential distribution with a mean of 45 seconds. Remember that the inverse formula for the exponential distribution is the natural log (ELN). Take the natural log of the random number and multiply that by the mean of the distribution, remembering to make the whole thing negative. Use the spreadsheet you built before, but add a column after the interarrival random times to calculate the arrival time. Use the Service random values as the service times for each customer. Determine the Start-of-Service and End-of-Service times for each customer. For output, calculate the Wait Times (in minutes) for each customer and the average wait time for the 90 customers. Also find the maximum wait, and the number of customers waiting less than 1 minute, between 1 and 5 minutes, and greater than 10 minutes. Create a data table the does 50 replications of the simulation for all those outputs. Average the 50 replications. Determine a 95% confidence interval for the average wait time. Do all of this before considering the What-If scenarios below. You should end up with a spreadsheet that looks very much like the lecture note and example spreadsheets. Now, create a copy of the spreadsheet you just made, and copy the random numbers provided in Blackboard (Random Number Spreadsheet for In-Class Daily Quiz) in place of the random numbers you generated using the "=RANDO function. That way, you all have the same output, but it makes the Data Table and Confidence Interval tabs irrelevant. For the What-If Scenarios, I recommend making copies of the Simulation tab, using the "fixed values for the random numbers, and changing the parameters. Do not bother with the Data Tables or Confidence Intervals. What-If Scenarios Raising your prices would decrease the number of customers you have. Change the maximum arrival time from 30 to 40, and delete the last 10 customers (change the number of customers from 90 to 80). Do not repeat the confidence interval calculation, but look at the average outputs from the simulation to decide whether or not it is worthwhile driving away 10 customers. Options for reducing the service time are: o Decrease options (reduce mean service time from 45 seconds to 35 seconds) o Hire an assistant (reduce mean service time from 45 seconds to 25 seconds) o Prepare foods in advance instead of making fresh (reduce mean service time from 45 seconds to 30 seconds) Run each option and discuss the relative costs (think like a business person) and benefits (from the averages of the data table). Copy these random numbers into columns on your spreadsheet and then use them instead of the RANDO) Random Numbers for Arrival Simulation 0.5660 0.9932 0.6454 0.2416 0.7609 0.2540 0.8054 0.8518 0.3790 0.1380 0.4346 0.9573 0.5670 0.6838 0.1686 0.1568 0.4391 0.5669 0.1762 0.3561 0.5260 0.3894 0.2744 0.3401 0.1844 0.9398 0.8638 0.1429 0.5466 0.2965 0.8650 0.1888 0.7299 0.1493 0.9620 0.6523 0.5296 0.8364 0.9502 0.9807 0.5096 0.9827 0.2404 0.0530 0.7812 0.3914 0.3488 0.4997 0.2905 0.1704 0.6235 0.5145 0.4331 Random Numbers for Service Simulation 0.0657 0.7628 0.9676 0.5660 0,1268 0.4897 0.4176 0.7284 0.9146 0.0111 0.1706 0.2364 0.3487 0.6770 0.1465 0.0502 0.7912 0.7731 0.7636 0.7545 0.0341 0.5286 0.8825 0.8254 0.5512 0.2951 0.2431 0.8153 0.7202 0.4548 0.6778 0.0913 0.4913 0.8625 0.6665 0.5173 0.3505 0.7424 0.2896 0.9196 0.0509 0.2318 0.1649 0.2725 0.1946 0.8746 0.2643 0.8368 0.6815 0.4477 0.0468 0.6481 0.7299 0.2967 0.6983 0.4879 0.6762 0.7678 0.0249 0.4763 0.4019 0.5283 0.4256 0.5656 0.4267 0.8990 0.7533 0.8879 0.3083 0.3785 0.8120 0.9676 0.6090 0.4493 0.9385 0.4005 0.4203 0.7235 0.7240 0.9863 0.2650 0.2194 0.9776 0.6912 0.3070 0.8321 0.9048 0.5355 0.6931 0.3171 0.9650 0.2357 0.8007 0.8742 0.6673 0.4110 0.8125 0.4771 0.2849 0.5777 0.7546 0.4556 0.4607 0.5444 0.8520 0.6660 0.5724 0.0716 0.0834 0.5471 0.7711 0.2299 0.3364 0.3107 0.1295 0.6260 0.5209 0.5797 0.0430 0.9175 0.8802 0.7003 0.4895 0.9977 0.5676 0.4246 0.1911