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FORCASTING
Month Time Q
Jan 1 46
Feb 2 56
Mar 3 72
Apr 4 67
May 5 77
Jun 6 66
Jul 7 69
Aug 8 79
Sep 9 88
Oct 10 91
Nov 11 94
Dec 12 104
Jan ?
Feb ?
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- is the world heading for a recession? explain the conditons under which the world can be classified as being in a recession as COVID-19 persists. explain linking the pandemic to the various stages of a recessionCovid-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?Lauren’s Beauty Boutique has experienced the followingweekly sales: Week Sales1 4322 3963 4154 4585 460 Forecast sales for week 6 using the naïve method, a simpleaverage, and a three-period moving average
- Metropolitan Hospital has estimated its average monthly bed needs asN = 1;000 + 9Xwhere X = time period (months); January 2002 = 0N = monthly bed needsAssume 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:MONTH ADJUSTMENT FACTOR (%)January +5April −15July +4November −5December −25a. Forecast Metropolitan’s bed demand for January, April, July, November, and December 2007.b. 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?YEAR FORECAST ACTUAL2007 1,045 1,0962006 937…Raul is the marketing manager for a line of skin care products targeted to males between 16 and 35 who have active outdoor lifestyles. He has found through market research the the price elasticity for his most popular sunscreen, which is priced at $22.00 for a 6 oz. tube, is -1.20. Last year Raul sold 125,000 units of the sunscreen. Raul is considering a price reduction on the sunscreen to $18.00. His manager has asked Raul for a forecast of the units he should expect to sell at the reduced price. What forecast should Raul provide to his manager? Group of answer choices about 145.000 units about 130,000 units about 152,000 units about 27,000 unitsMr. Geppetto uses exponential smoothing to predict revenue in his wood carving business. He uses a weight of = .4 for the naïve forecast and (1-) = .6 for the past forecast. What revenue did he predict for March using the data below? MONTH REVENUE FORECAST Nov 100 100 Dec 90 100 Jan 115 ---- Feb 110 ---- MARCH ? ?
- Based on the past data, forecast demand for the next three years for a tyre company.Demand function: Qdt = 160 − 0.8PtSupply function: Qst = -20 + 0.4Pt−1and when P0 = 160a) A good should be designed in accordance with demand and supply,The equilibrium price is 160. Find the time path of the equilibrium price of this good.b) Comment on the use of this time path. Draw the passage of the time path.find AWx(10%) and AWy(10%)
- Suppose that you work for a U.S. senator who is contemplating writing a bill that would put a national sales tax in place. Because the tax would be levied on the sales revenue of retail stores, the senator has asked you to prepare a forecast of retail store sales for year 8, based on data from year 1 through year 7. The data are: (c1p2) Year Retail Store Sales 1 $1,225 2 1,285 3 1,359 4 1,392 5 1,443 6 1,474 7 1,467 54 Chapter One a. Use the first naive forecasting model presented in this chapter to prepare a forecast of retail store sales for each year from 2 through 8. b. Prepare a time-series graph of the actual and forecast values of retail store sales for the entire period. (You will not have a forecast for year 1 or an actual value for year 8.) c. Calculate the root-mean-squared error for your forecast series using the values for year 2 through year 7. 3. Use the second naive forecasting model presented in this chapter to answer parts (a) through (c) of Exercise 2. Use P 0.2 in…Tom Glass forecasts electrical demand for the Flatlands Public Power District (FPPD). The FPPD wants to take its Comstock power plant out of service for maintenance when demand is expected to be low. After shutdown, performing maintenance and getting the plant back on line takes two weeks. The utility has enough other generating capacity to satisfy 1,550 megawatts (MW) of demand while Comstock is out of service. Table shows weekly peak demands (in MW) for the past several autumns. When next in year 6 should the Comstock plant be scheduled for maintenance?Diego needs to forecast demand for his company's products, using the data he already possesses. He has an average of previous demand, and he knows the most recent demand because he believes it's a better predictor of future demand. Which forecasting technique should he use?