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The head of Patient Escort Services for Vancouver General Hospital (VGH) had to determine the best approach to improve efficiency of the hospital's porter system. Porters represented a vital part of various hospital processes, facilitating timely flow of patients, equipment and materials throughout the hospital. Recently, VGH had experienced incidents in which the capacity of the porters was insufficient to meet the demands of the hospital and, despite best-efforts at scheduling, these problems remained. The head of Patient Escort Services spent several weeks collecting data to determine where the problems existed, and wondered if his data could provide answers to some critical questions: How well did the current porter schedule meet daily demand? What is the optimum number of porters? The head of Patient Escort Services had one week to submit his report to VGH's board of directors.

A student is trying to incorporate various analytical tools to assist in selecting National Hockey League (NHL) players to a fantasy hockey pool, using individual player data from the NHL seasons 2006 to 2009. The student must come up with a strategy in which 16 players are selected for the 2010 season.

This note complements Note on Logistic Regression, product #9B10E005 and Note on Logistic Regression - The Binomial Case, product #9B10E012. The focus of this note is to show how to calculate the associated p-values of the estimated beta coefficients using Microsoft Excel. It also illustrates the procedure based on the example from the Note on Logistic Regression - The Binomial Case.

This note complements Note on Logistic Regression, product #9B10E005 and Note on Logistic Regression - The Binomial Case, product #9B10E012. The focus of this note is to show how to calculate the associated p-values of the estimated beta coefficients using Microsoft Excel. It also illustrates the procedure based on the example from the Note on Logistic Regression - The Binomial Case.

A professor is considering buying a new car and is evaluating two models, one with air conditioning and a comfort package, the other with no extras. The two cars are relatively close in price but still above his initial budget, and he is wondering how much he might be able to negotiate the price. A factor that complicates the matter is that the car with the comfort package has a lower interest rate. The professor therefore needs to understand what the net present value of the difference in the two payment plans is.

A professor is considering buying a new car and is evaluating two models, one with air conditioning and a comfort package, the other with no extras. The two cars are relatively close in price but still above his initial budget, and he is wondering how much he might be able to negotiate the price. A factor that complicates the matter is that the car with the comfort package has a lower interest rate. The professor therefore needs to understand what the net present value of the difference in the two payment plans is.

One of the most basic revenue management problems is how to allocate a fixed capacity to various types of classes of customers so that the total profit is maximized. Using the example of a flight traveling from Toronto to Vancouver, the revenue management problem is to decide, in each period, how much of the realized demand to accept and how much to reserve for the latter classes in order maximize the revenue. The crux of the problem revolves around the trade-off between spoilage and dilution. The author uses various mathematical formulae (including the static model, Littlewood's Two-Class model and n-Class model of expected marginal seat revenue) to model optimal seat-allocation outcomes.

Due to continued budget shortfalls the project manager for the Spinal Cord Rehabilitation Program at the Toronto Rehabilitation Institute needed to provide proposals for immediate cost-saving measures. One of these measures included how to schedule the nursing staff. The problem involved meeting certain occupancy target levels while ensuring a minimum number and correct mix of available nurses.

Excel spreadsheet for students.

The head of Patient Escort Services for Vancouver General Hospital (VGH) had to determine the best approach to improve efficiency of the hospital's porter system. Porters represented a vital part of various hospital processes, facilitating timely flow of patients, equipment and materials throughout the hospital. Recently, VGH had experienced incidents in which the capacity of the porters was insufficient to meet the demands of the hospital and, despite best-efforts at scheduling, these problems remained. The head of Patient Escort Services spent several weeks collecting data to determine where the problems existed, and wondered if his data could provide answers to some critical questions: How well did the current porter schedule meet daily demand? What is the optimum number of porters? The head of Patient Escort Services had one week to submit his report to VGH's board of directors.

Due to continued budget shortfalls the project manager for the Spinal Cord Rehabilitation Program at the Toronto Rehabilitation Institute needed to provide proposals for immediate cost-saving measures. One of these measures included how to schedule the nursing staff. The problem involved meeting certain occupancy target levels while ensuring a minimum number and correct mix of available nurses.