What is the information you need? Would you mind give me detail?

This all information I got.

Below are simulated data of a hypothetical line of customers from 9:00 to 9:30 AM. The customers arrived at the line, got their paperwork checked, and exited the line. Some of the customers arrived in groups of two, three, or more and exited together. There were more than one agents who checked the paperwork. Customer ID Arrival Time Exit Time Notes 9:00:21 This customer arrived earlier than 9:00AM 9:00:55 This customer arrived earlier than 9:00AM 9:00:06 9:00:59 9:01:13 9:02:20 9:02:05 9:03:16 9:02:46 9:03:48 9:02:46 9:03:48 9:02:46 9:03:42 9:02:58 9:03:55 9:02:59 9:04:05 9:05:48 9:06:40 9:05:56 9:06:55 9:05:56 9:06:55 9:05:56 9:06:55 9:08:14 9:09:24 9:08:47 9:09:51 9:09:00 9:09:51 9:10:03 9:11:07 9:11:02 9:11:59 9:11:23 9:12:23 9:12:48 9:13:36 9:12:59 9:13:45 9:13:56 9:15:04 9:14:29 9:15:30 9:14:54 9:15:59 9:15:29 9:16:19 9:16:03 9:17:06 9:17:09 9:18:36 9:17:09 9:18:36 9:17:19 9:18:25 9:17:30 9:18:28 9:17:40 9:18:51 9:17:47 9:18:41 9:18:00 9:18:57 9:18:29 9:19:45 9:19:52 9:20:51 9:19:54 9:20:55 9:19:59 9:20:55 9:20:32 9:21:34 9:22:15 9:23:18 9:22:15 9:23:18 9:24:28 9:25:32 9:24:36 9:25:59 9:25:37 9:26:30 9:25:37 9:26:37 9:25:40 9:26:36 9:26:15 9:27:24 9:26:15 9:27:24 9:26:15 9:27:24 9:28:27 This customer exited later than 9:30 AM 9:28:55 9:29:36 This part would help you to reinforce your understanding of the Little's Law. We have a hypothetical situation where customers arrived at a line, got their paperwork checked, and exited the line. In addition, we recorded this paperwork checking process from 9:00 to 9:30AM. The simulated data are in the Excel file TOM3010_OM_Project_Part2_Data.xlsx which can be found together with this Project Description on Blackboard. Based on these data, you would need to calculate the three fundamental metrics of the process and check to what extent they follow the Little's Law. Essentially, you would practice with calculating averages. As how you would record processes in the reality, the simulated data include time stamps of arrivals and exits. With this recording method, you can deal with complications like some customers might arrive in groups and some customers might arriver earlier or exit later than the recording time window. Thus, this exercise can be applied to many real-life processes. In your report of this part, you need to present the following: (a) Based on the data, define and independently calculate the three fundamental metrics: observed average inventory (customers), observed average flow rate (customers per minute), and observed average flow time (minutes). Please show how you calculate these metrics and use 3 decimal places in the final results. You may copy work from Excel. These calculations were discussed in class. Just refer to the banking example in Module 03 - Slide 22. Especially, to find the observed average inventory, you would need to divide the recording time window into a grid of points in time, the finer the grid the better. The minimum is one point for every minute. (b) Using the Little's Law, calculate the predicted average inventory (customers). Then, present the following table with all four values (3 decimal places): | Value 1 Observed average inventory (number of customers in line) Value 2 Observed average flow rate (number of through customers per minute) Value 3 Observed average flow time (number of minutes waiting in line) Value 4 Calculated average inventory (number of customers in line) (c) Calculate the percentage difference between Value 1 and Value 4, e.g. 100%*(V1-14)/(4. Then make a statement on how close these two values are. If Value 1 and Value 4 differ by a large margin (more than 5%), discuss possible reasons for the difference and corresponding approaches to narrow the gap. Please feel free to discuss the difficulties that you find. Below are simulated data of a hypothetical line of customers from 9:00 to 9:30 AM. The customers arrived at the line, got their paperwork checked, and exited the line. Some of the customers arrived in groups of two, three, or more and exited together. There were more than one agents who checked the paperwork. Customer ID Arrival Time Exit Time Notes 9:00:21 This customer arrived earlier than 9:00AM 9:00:55 This customer arrived earlier than 9:00AM 9:00:06 9:00:59 9:01:13 9:02:20 9:02:05 9:03:16 9:02:46 9:03:48 9:02:46 9:03:48 9:02:46 9:03:42 9:02:58 9:03:55 9:02:59 9:04:05 9:05:48 9:06:40 9:05:56 9:06:55 9:05:56 9:06:55 9:05:56 9:06:55 9:08:14 9:09:24 9:08:47 9:09:51 9:09:00 9:09:51 9:10:03 9:11:07 9:11:02 9:11:59 9:11:23 9:12:23 9:12:48 9:13:36 9:12:59 9:13:45 9:13:56 9:15:04 9:14:29 9:15:30 9:14:54 9:15:59 9:15:29 9:16:19 9:16:03 9:17:06 9:17:09 9:18:36 9:17:09 9:18:36 9:17:19 9:18:25 9:17:30 9:18:28 9:17:40 9:18:51 9:17:47 9:18:41 9:18:00 9:18:57 9:18:29 9:19:45 9:19:52 9:20:51 9:19:54 9:20:55 9:19:59 9:20:55 9:20:32 9:21:34 9:22:15 9:23:18 9:22:15 9:23:18 9:24:28 9:25:32 9:24:36 9:25:59 9:25:37 9:26:30 9:25:37 9:26:37 9:25:40 9:26:36 9:26:15 9:27:24 9:26:15 9:27:24 9:26:15 9:27:24 9:28:27 This customer exited later than 9:30 AM 9:28:55 9:29:36 This part would help you to reinforce your understanding of the Little's Law. We have a hypothetical situation where customers arrived at a line, got their paperwork checked, and exited the line. In addition, we recorded this paperwork checking process from 9:00 to 9:30AM. The simulated data are in the Excel file TOM3010_OM_Project_Part2_Data.xlsx which can be found together with this Project Description on Blackboard. Based on these data, you would need to calculate the three fundamental metrics of the process and check to what extent they follow the Little's Law. Essentially, you would practice with calculating averages. As how you would record processes in the reality, the simulated data include time stamps of arrivals and exits. With this recording method, you can deal with complications like some customers might arrive in groups and some customers might arriver earlier or exit later than the recording time window. Thus, this exercise can be applied to many real-life processes. In your report of this part, you need to present the following: (a) Based on the data, define and independently calculate the three fundamental metrics: observed average inventory (customers), observed average flow rate (customers per minute), and observed average flow time (minutes). Please show how you calculate these metrics and use 3 decimal places in the final results. You may copy work from Excel. These calculations were discussed in class. Just refer to the banking example in Module 03 - Slide 22. Especially, to find the observed average inventory, you would need to divide the recording time window into a grid of points in time, the finer the grid the better. The minimum is one point for every minute. (b) Using the Little's Law, calculate the predicted average inventory (customers). Then, present the following table with all four values (3 decimal places): | Value 1 Observed average inventory (number of customers in line) Value 2 Observed average flow rate (number of through customers per minute) Value 3 Observed average flow time (number of minutes waiting in line) Value 4 Calculated average inventory (number of customers in line) (c) Calculate the percentage difference between Value 1 and Value 4, e.g. 100%*(V1-14)/(4. Then make a statement on how close these two values are. If Value 1 and Value 4 differ by a large margin (more than 5%), discuss possible reasons for the difference and corresponding approaches to narrow the gap. Please feel free to discuss the difficulties that you find