a. How many nurses should be working each month to most closely match patient forecasts? b. Suppose the hospital does not want to change its policy of not increasing the nursing staff size by more than 10 percent in any month. Suggest a schedule of nurse staffing over the four months that meets this requirement and also meets the need for nurses each month.
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a. How many nurses should be working each month to most closely match patient
b. Suppose the hospital does not want to change its policy of not increasing the nursing staff size by more than 10 percent in any month. Suggest a
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- The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
- The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?Suppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.The file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?
- The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?1. Which of the following exactly defines continuous processes? - Continuous processes are able to produce very high volumes of outputs. - Continuous processes are able to produce very low volumes of outputs. - Continuous processes are able to produce very high volumes of fully standardized outputs. - Continuous processes are able to produce very high volumes of low standardized outputs. 2. A company produces plastic glasses and wants to use exponential smoothing for forecasting. It is known that demand forecast in the last period (t-1) was 400 glasses while actual demand (t-1) was 380. It is also known that actual demand in the current period (t) will be 550 glasses. Exponential smoothing coefficient (α) is 0.30. Make a forecast for the next period (t+1). - 510 - 394- 440 -441 3. Which of the following is considered to be the most critical driving force of continuous quality improvement in TQM philosophy? - PDSA cycle - Malcolm Baldridge Quality Award Model - quality function…The Holt method (exponential smoothing with trend andwithout seasonality) is being used to forecast weekly carsales at TOD Ford. Currently, the base is estimated to be 50cars per week, and the trend is estimated to be 6 cars perweek. During the current week, 30 cars are sold. Afterobserving the current week’s sales, forecast the number ofcars to be sold during the week that begins three weeks afterthe conclusion of the current week. Use a b 0.3.
- Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: Year 1 2 3 4 5 6 7 8 9 10 11 Registrations (000) 5.00 6.00 3.00 5.00 10.00 8.00 8.00 9.00 11.00 16.00 17.00 Part 2 a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a smoothing constant (α) of 0.40 and a starting forecast of 6.00 for year 1 (round your responses to one decimal place): Year 1 2 3 4 5 6 7 8 9 10 11 12 Forecast (000) 6.00 enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter…Mike Thatcher is a sales manager for an automobile dealership in Alberta. Mike earns a bonus each year based on revenue generated by the number of vehicles sold in the year less related warranty expenses. The quality of automobiles sold each year seems to vary since the warranty experience related to vehicles sold is highly variable. The actual warranty expenses have varied over the past 10 years from a low of 3% of an automobile’s selling price to a high of 10%. In the past, Mike has tended toward estimating warranty expenses on the high end just to be prudent. It is the end of the year and once again he must work with the dealership’s accountant in arriving at the warranty expense accrual for the cars sold this year. Required 1. Does the warranty accrual decision present any kind of ethical dilemma for Mike Thatcher? 2. Since the warranty experience is not constant, what percent do you think Mike should choose for this year? Justify your response.A restaurant wants to forecast its weekly sales. Historical data (in dollars) for 15 weeks are shown in this Excel file (also shown in Problem 6 on page 243 in the textbook). Answer the following questions related to this information: What is the MSE for the two- and three-period moving average models? Compare the results. Find the best number of periods for the moving average model based on MSE.