Given a budget of $300 and the following data on three components that must operate in series, determine, using marginal analysis, the optimum number of redundant units. Compute the achieved reliability. Component 1 2 23 3 Reliability 0.9 0.8 0.7 Unit Cost $100 50 20
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- 6. An economist studies the relationship betweenthe price (x) and weekly demand (y) of a certainproduct. Assume the SLR model utility test findsevidence of a linear relationship between priceand demand. Find the appropriate intervalestimate for the mean demand for all weekswhen the price is $31. We know: n = 5 , X-bar = 30,sx2 = 10 , MSE = 12.1 , and Y-hat = 181 − 2.7x.need helpFollowing are two weekly forecasts made by two different methods for the number of gallons of gasoline, in thousands, demanded at a local gasoline station. Also shown are actual demand levels, in thousands of gallons: Week 234 Forecast Method 1 The MAD for Method 1 = 0.85 1.02 0.97 1.20 Actual Demand 0.72 1.05 1.07 1.00 Week 1 2 3 4 Forecast Method 2 0.77 1.21 0.88 1.15 thousand gallons (round your response to three decimal places). Actual Demand 0.72 1.05 1.07 1.00
- The problem is based on the following data given. Observations of the demand for a certain part stocked at a parts supply depot during the calendar year 2013 were ( as shown ). What would an MA(1) forecasting method mean? Compare the accuracy of MA(1) and MA(4) forecasts for July through December 2013.As a sales analyst for the shoe retailer Foot Locker, one of your responsibilities is measuring store productivity and then reporting your conclusion back to management. Foot Locker uses sales per square foot as a measure of store productivity. While preparing your report for the second quarter results (Q2), you are able to determine that annual sales for last year ran at a rate of $406 per square foot. Therefore, $406 per square foot will be your sales estimate for the population of all Foot Locker stores during Q2. For your Q2 Sales Report, you decide to take a random sample of 64 stores. Using annual data from last year, you are able to determine that the standard deviation for sales per square foot for all 3,400 stores was $80. Therefore $80 per square foot will be your population standard deviation when compiling your Q2 report. Management has asked for the probability that your sample mean based on 64 stores is 1) within $15 and 2) within $5 of the population mean…a and b
- Table 1. The manager of Carpet City outlet store needs to be able to forecast accurately demand for Soft Shang carpet. Demand for the past 20 weeks appears in table 1 below. week Demand Forecast Error ABS. Dev Squared Error APE 1 20 2 28 3 22 4 18 5 22 6 22 7 22 8 26 9 23 10 23 11 23 12 27 13 25 14 22 15 23 16 14 17 14 18 15 19 11 20 16 21 22 23 24…The following are historical demand data: ACTUAL YEAR 2011 SEASON DEMAND Spring 201 Summer 142 Fall 380 Winter 578 2012 Spring 469 Summer 273 Fall Winter 683 963 Use regression analysis on deseasonalized demand to forecast demand in summer 2013. (Do not round intermediate calculations. Round your answer to the nearest whole number.) Forecast for summer 20132.) Consider an M/M/2 system with an arrival rate of 9 per minute and a service rate of 8 per minute. What is the average time a customer spends in the system? Take your answer to three decimal places. Omit the units in your answer.
- A manufacturer has the following data on the variation of its prices in relation to the quantity demanded: at a unit price of $ 78.00, the quantity demanded is 1200 units. With a 36% increase in price, the quantity demanded drops to 28.08 units. To determine: a) The amount that must be needed for a recipe to be maximum, a amount received maximum and the unit price. b) Determine in which quantity sold intervals the revenue is increasing and decreasing.Develop a three-period moving average forecast for periods 13-15. Period 10 11 12 13 14 Demand 265 359 436 261 462 Calculate the forecasts for periods 13-15 by using a three-period moving average model (enter your responses rounded to the nearest whole number). Period Demand Forecast 10 265 11 359 12 436 13 261