Saint Leo University Queuing Analysis Discussion

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Part 1

The following problems are due for Module 3:

Queuing Analysis (Chapter #13) Problem# 4,6, 8,10

Please submit one Excel file containing separate worksheet (tab) for each problem.

Problem 4.) The ticket booth on the Tech campus is operated by one person, who is selling tickets for the annual Tech versus State football game on Saturday. The ticket seller can serve an average of 12 customers per hour; on average, 10 customers arrive to purchase tickets each hour (Poisson distributed). Determine the average time a ticket buyer must wait and the portion of time the ticket seller is busy.

Problem 6.) The Dynaco Manufacturing Company produces a particular product in an assembly line operation. One of the machines on the line is a drill press that has a single assembly line feeding into it. A partially completed unit arrives at the press to be worked on every 7.5 minutes, on average. The machine operator can process an average of 10 parts per hour. Determine the average number of parts waiting to be worked on, the percentage of time the operator is working, and the percentage of time the machine is idle.

Problem 8.) The Peachtree Airport in Atlanta serves light aircraft. It has a single runway and one air traffic controller to land planes. It takes an airplane 12 minutes to land and clear the runway. Planes arrive at the airport at the rate of 4 per hour.

  1. Determine the average number of planes that will stack up, waiting to land.
  2. Find the average time a plane must wait in line before it can land.
  3. Calculate the average time it takes a plane to clear the runway once it has notified the airport that it is in the vicinity and wants to land.
  4. The FAA has a rule that an air traffic controller can, on average, land planes a maximum of 45 minutes out of every hour. There must be 15 minutes of idle time available to relieve the tension. Will this airport have to hire an extra air traffic controller?

Problem 10.) During registration at State University every semester, students in the college of business must have their courses approved by the college adviser. It takes the adviser an average of 2 minutes to approve each schedule, and students arrive at the adviser’s office at the rate of 28 per hour.

  1. A.)Computer L, Lq, W, Wq, and U.
  2. B.)The dean of the college has received a number of complaints from students about the length of time they must wait to have their schedules approved. The dean feels that waiting 10.00 minutes to get a schedule approved is not unreasonable. Each assistant the dean assigns to the adviser’s office will reduce the average time required to approve a schedule by 0.25 minute, down to a minimum time of 1.00 minute to approve a schedule. How many assistants should the dean assign to the adviser?

Part 2 (A) Use at least 2 references that are websites and based in the United States. Must be between 300-500 words these are discussion responses.

There are all sorts of strategies that can be used to help businesses understand information. Analytics in particular can be separated into different categories, like descriptive, predictive, and prescriptive. The first of these can be described as studying data in order to interpret the current state of a business through extensive details (Adair, 2022). Descriptive analytics often involve the research of a business’ history to understand how present-day statistics have come to be where they are now and what the current numbers mean (Adair, 2022).

To exemplify descriptive analytical techniques, quantitative tables that display annual revenue amounts, monthly sales reports, return on investment, etc. are what will typically be used (Frankenfield, 2020). These examples point back to the point of descriptive analytics, which is to interpret the history of a company’s data in order to find any changes and figure out how past numerical figures factor into present-day statistics (Frankenfield, 2020).

Predictive analytics, on the other hand, are meant to look at the same data that descriptive analytics use but are instead meant to determine future outcomes and business performance rather than analyze the current numbers (Halton & Rasure, 2021). It is done to adjust where the resources for future events should be allocated in order to increase efficiency and reduce risk (Halton & Rasure, 2021). An example of real-life predictive analytics is weather forecasts, which use current data meteorologists have for present and past weather patterns in order to predict what the weather will look like within a certain area over the upcoming hours and days (Halton & Rasure, 2021).

Finally, prescriptive analytics utilize data in order to uncover how to achieve desired objectives (Rathburn & Segal, 2021). It involves using existing data to factor them into how to configure potential situations or scenarios the business may find itself in the future to ultimately decide what the best strategy to take would be (Rathburn & Segal, 2021). A common example of prescriptive analytics in use are algorithms that businesses use, which involve using technology to compute calculations and solve problems to map out potential plans (Rathburn & Segal, 2021). In a way, basic arithmetic can be considered prescriptive analytics since using simple math factors into figuring out potential future outcomes (Rathburn & Segal, 2021). Instead of simply trying to forecast an accurate future scenario and leaving it at that like predictive analytics, prescriptive analytics aim to find the best scenario from calculations and inspire further action to make it happen.

References

Adair, B. (2022, Aug. 20). Descriptive vs. Predictive vs. Prescriptive vs. Diagnostic Analytics. SelectHub. Retrieved from: https://www.selecthub.com/business-intelligence/predictive-descriptive-prescriptive-analytics/

Frankenfield, J. (2020, Dec. 29). Descriptive Analytics. Investopedia. Retrieved from: https://www.investopedia.com/terms/d/descriptive-analytics.asp#:~:text=Examples%20of%20metrics%20used%20in,as%20predictive%20and%20prescriptive%20analytics.

Halton, C., Rasure, E. (2021, Jun. 30). Predictive Analytics. Investopedia. Retrieved from: https://www.investopedia.com/terms/p/predictive-analytics.asp

Rathburn, P., Segal, T. (2021, Jul. 25). What is Prescriptive Analytics? Investopedia. Retrieved from: https://www.investopedia.com/terms/p/prescriptive-analytics.asp

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Part 2 (B) Use at least 2 references that are websites and based in the United States. Must be between 300-500 words these are discussion responses.

Descriptive analytics can tell you about what happened in the past. Descriptive analytics is important when it comes to understanding how a business performs. It can do that by providing context and interpreting information for stakeholders. Descriptive analytics includes data visualization in forms of graphs, charts, reports, and dashboards. A common real-world example would be in healthcare. For example, when there are many people coming into the emergency room in the span of a few hours. Descriptive analytics allows us to see what was happening and provide all the necessary data (Comparing descriptive, predictive, prescriptive, and diagnostic analytics, 2022).

Predictive analytics is all about taking historical data and addressing key trends or patterns. The data is then applied current data to try and see what can or will happen in the future. With hospitals, they can try to see when their will be a high number of patients. This can be based on the data that was collected from previous years and illness spreading at a high rate (Comparing descriptive, predictive, prescriptive, and diagnostic analytics, 2022).

Prescriptive analytics is somewhat of a step up from predictive analytics. It gives various courses of action and outlines of what potential implications would be. Back to the example with high illness rates with hospital visits. Now with the information about trends of illness spreading we can use prescriptive analytics to determine staffing numbers (Comparing descriptive, predictive, prescriptive, and diagnostic analytics, 2022).

Overall, descriptive analytics looks at the past to determine what happened and why. While predictive and prescriptive analytics uses past data to determine what will or could happen. Along with what to do when those things happen (Comparing descriptive, predictive, prescriptive, and diagnostic analytics, 2022).

Comparing descriptive, predictive, prescriptive, and diagnostic analytics. insightsoftware. (2022, July 13). Retrieved September 15, 2022, from https://insightsoftware.com/blog/comparing-descrip…

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