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- Describe how you might address the uncertainty associated with the projectProblems?Define the term expected return?Q4 A business manager determines that t months after production begins on a new product, the number of units produced will be P thousand,where P(t) =6?2 + 5? /(? + 1)2 production in the long run (i) A ruptured pipe in a North Sea oil rig produces a circular oil slick that is y meters thick at a distance x meters from the rupture.Turbulence makes it difficult to directly measure the thickness of the slick at the source (where x = 0),but for x > 0,it is found that y =0.5(x2 + 3x)/ x3 + x2 + 4x Required:a)Assuming the oil slick is continuously distributed,how thick would you expect it to be at the source?
- Bell Greenhouses has estimated its monthly demand for potting soil to be the following: N=400+4X where N=monthlydemandforbagsofpottingsoil X=timeperiodsinmonths(March2006=0) Assume this trend factor is expected to remain stable in the foreseeable future. The following table contains the monthly seasonal adjustment factors, which have been estimated using actual sales data from the past five years: Forecast Bell Greenhouses demand for potting soil in March, June, August, and December 2007. If the following table shows the forecasted and actual potting soil sales by Bell Greenhouses for April in five different years, determine the seasonal adjustment factor to be used in making an April 2008 forecast.Metropolitan Hospital has estimated its average monthly bed needs as N=1,000+9X where X=timeperiod(months);January2002=0 N=monthlybedneeds Assume that no new hospital additions are expected in the area in the foreseeable future. The following monthly seasonal adjustment factors have been estimated, using data from the past five years: Forecast Metropolitans bed demand for January, April, July, November, and December 2007. If the following actual and forecast values for June bed demands have been recorded, what seasonal adjustment factor would you recommend be used in making future June forecasts?The Questor Corporation has experienced the following sales pattern over a 10-year period: Compute the equation of a trend line (similar to Equation 5.4) for these sales data to forecast sales for the next year. (Let 2004=0,2005=1, etc., for the time variable.) What does this equation forecast for sales in the year 2014? Use a first-order exponential smoothing model with a w of 0.9 to forecast sales for the year 2014.
- A firm experienced the demand shown in the following table. *Unkown future value to be forecast Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (with a w=0.9 and a w=0.3). Note The exponential smoothing forecasts may be begun by assuming Y t+1=Yt. Using the forecasts from 2005 through 2009, compare the accuracy of each of the forecasting methods based on the RMSE criterion. Which forecast would you have used for 2010? Why?Why is Afghanistan in recession due to COVID-19?Can you explain what these two belows mean in regard of GMM and Maximum likelihood. What are we calculating and what is it used to Unconstrained optimizationConstrained optimizatio
- a. In the Bayside Fountain Hotel problem, compute an exponentially smoothed forecast with an α value of .20. According to the result from Excel and/or POM-QM, the forecast for the year 10 would be b. In the Bayside Fountain Hotel problem, for the exponentially smoothed forecast with an α value of .20, compute the mean absolute deviation (MAD) via Excel and/or POM-QM. c. In the Bayside Fountain Hotel problem, compute an adjusted exponentially smoothed forecast with α = .20and β = .20. According to the result from Excel and/or POM-QM, the forecast for the year 4 would be d.Covid-19 backed by Lockdown generated many economic anomalies. The weeklychange in the price of the mask in a town is given below.Time March1 stweekMarch2 ndweekMarch3 rdweekMarch4 thweekApril1 stweekApril2 ndweekApril3 rdweekApril4 thweekMay1 stweek Price(₹)100 150 175 200 200 175 70 50 50Forecast the Expected price of Mask for the 2 nd week of May.Strangely the Actual price of Mask in the city in the 2 nd week of May was 10 rupees.State at least four economic reasons why your calculated Expected price of Mask didnot match the Actual price of Mask.Now assume when the price of the Mask was 200 rupees per unit 5 lakh customersbought it. As the price reduced to 50 rupees only 1 lakh customers bought it.Calculate elasticity of demand and state which laws of economics are violated in thiscase, and how?What are the critical points of CES function with A=100, α= 0.2 ß= -0.5 subject to the constaint 7K+16L=5200? A) K=2,32,L=232,58 B)K=3,23,L=323,58 C)K=4,32,L=432,58 D)K=4,23,L=423,58