The Monthly demand for unit manufactured by the ABC Company has been as follows:Units250290240280300270290 MonthJanuaryFebruaryMarchAprilMayJuneJuly a.use a four-week weighted moving average to forecast the units of month august by using weights of 40%, 30%, 20% & 10% respectively.b. use exponential smoothing with α=0.3 to forecast the units of month august.c. calculate the mad & mse (use exponential smoothing method). 1. The Monthly demand for unit manufactured by the ABC Company has been as follows:Units250290240280300270290MonthJanuaryFebruaryMarchAprilMayJuneJulya. Use a four-week weighted moving average to forecast the units of Month August byusing weights of 40%, 30%, 20% & 10% respectively. (08)b. Use exponential smoothing with a=0.3 to forecast the units of Month August.c. Calculate the MAD & MSE (use Exponential Smoothing method).

Here, we are provided with a monthly data. Now, we know that, 4 weeks constitute of a month.…

The Monthly demand for unit manufactured by the ABC Company has been as follows: Units 250 290 240 280 300 270 290 Month January February March April May June July a.use a four-week weighted moving average to forecast the units of month august by using weights of 40%, 30%, 20% & 10% respectively. b. use exponential smoothing with α=0.3 to forecast the units of month august. c. calculate the mad & mse (use exponential smoothing method).

The Monthly demand for unit manufactured by the ABC Company has been as follows: Units 250 290 240 280 300 270 290 Month January February March April May June July a.use a four-week weighted moving average to forecast the units of month august by using weights of 40%, 30%, 20% & 10% respectively. b. use exponential smoothing with α=0.3 to forecast the units of month august. c. calculate the mad & mse (use exponential smoothing method).

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...

See similar textbooks

Similar questions

The values of Alabama building contracts (in $ millions) for a 12 -month period follow. 240 350 240 260 280 320 220 310 240 310 240 240 A. Compare the three-month moving average approach with the exponential smoothing forecast using a=0.2 (to 2 decimals). MSE (3-Month) _______ MSE ( a=0.2) __________ Using only the errors for months 4 to 12, the MSE for exponential smoothing is: MSE ( a=0.2) __________ C. Using the approach that provides more accurate forecasts based on MSE, what is the forecast for the next month (to the nearest whole number)? $ _______million
Table 1 HPF Demand in the last 12 periods Period Month Demand in '000 Period Month Demand in '000 1 January 37 7 July 43 2 February 40 8 August 47 3 March 41 9 September 56 4 April 37 10 October 52 5 May 45 11 November 55 6 June 50 12 December 54 The manager of the company wants to be certain enough OFC01 are available to complete orders promptly and they have adequate inventory in stock. During the last meeting, a number of forecast techniques have been discussed: Simple moving average n = 4 Weighted moving average with n=4 with the following weights from most recent periods: 0.4, 0.3, 0.2, 0.1 Exponential Smoothing with alpha = 0.2 Linear trend The manager would like to ascertain the best tools that he and his team can effectively manage the production processes. Among the above forecasting methods, which method should be used to forecast the demand for this product? Why? The…
Two pumps capable of delivering 100 hp to an agricultural application are being evaluated in a present economy study. The selected pump will only be utilized for one year, and it will have no market value at the end of the year. Pertinent data are summarized as given follows. If electric power costs $0.10 per kWh and the pump will be operated 4,000 hours per year, which pump should be chosen? Recall that 1 hp = 0.746 kW.
Storrs Cycles has just started selling the new Cyclonemountain bike, with monthly sales as shown in the table. First,co-owner Bob Day wants to forecast by exponential smoothingby initially setting February’s forecast equal to January’s saleswith a = .1. Co-owner Sherry Snyder wants to use a three-periodmoving average. a) Is there a strong linear trend in sales over time?b) Fill in the table with what Bob and Sherry each forecast forMay and the earlier months, as relevant.c) Assume that May’s actual sales figure turns out to be 405.Complete the table’s columns and then calculate the meanabsolute deviation for both Bob’s and Sherry’s methods.d) Based on these calculations, which method seems moreaccurate?
Monthly sales for a six month period are as follows: Month Sales Jan 18,000 Feb 22,000 Mar 16,000 Apr 18,000 May 20,000 June 24,000 Compute the sales forecast for July using the following approaches: (1) Four-month moving average; (2) Weighted three-month moving average using .50 for June, .30 for May and .20 for April; (3) Exponential smoothing with α (smoothing constant) equal to .40, assuming a February forecast of 18,000
With the gasoline time series data from the given table, show the exponential smoothing forecasts using = 0.1. Week Sales (1000s of gallons) 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of = 0.1 or = 0.2 for the gasoline sales time series? Do not round your interim computations and round your final answers to two decimal places. = 0.1 = 0.2 MSE fill in the blank 1 fill in the blank 2 Prefer: 01. or 0.2 2. Are the results the same if you apply MAE as the measure of accuracy? Do not round your interim computations and round your final answers to two decimal places. = 0.1 = 0.2 MAE fill in the blank 4 fill in the blank 5 Prefer: 0.1 or 0.2 3. What are the results if MAPE is used? Do not round your interim computations and round your final answers to two decimal places. = 0.1 = 0.2 MAPE fill in…
Ch 13. 3: Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to manage its inventory more effectively and make revenue projections, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 30 sales periods (each sales period is defined to be a four-week period). The demand data are presented in table below concerning y (demand for Fresh liquid laundry detergent), x1 (the price of Fresh), x2 (the average industry price of competitors' similar detergents), and x3 (Enterprise Industries’ advertising expenditure for Fresh). To ultimately increase the demand for Fresh, Enterprise Industries’ marketing department is comparing the effectiveness of three different advertising campaigns. These campaigns are denoted as campaigns A, B, and C. Campaign A consists entirely of television commercials, campaign B consists of a balanced mixture of television and…
Finally, the researcher considers using regression analysis to establish a linear relationship between the two variables – hours worked per week and yearly income. Hours per week Yearly Income ('000's) 18 43.8p 13 44.5 18 44.8 25.5 46.0 11.5 41.2 18 43.3 16 43.6 27 46.2 27.5 46.8 30.5 48.2 24.5 49.3 32.5 53.8 25 53.9 23.5 54.2 30.5 50.5 27.5 51.2 28 51.5 26 52.6 25.5 52.8 26.5 52.9 33 49.5 15 49.8 27.5 50.3 36 54.3 27 55.1 34.5 55.3 39 61.7 37 62.3 31.5 63.4 37 63.7 24.5 55.5 28 55.6 19 55.7 38.5 58.2 37.5 58.3 18.5 58.4 32 59.2 35 59.3 36 59.4 39 60.5 24.5 56.7 26 57.8 38 63.8 44.5 64.2 34.5 55.8 34.5 56.2 40 64.3 41.5 64.5 34.5 64.7 42.3 66.1 34.5 72.3 28 73.2 38…
Finally, the researcher considers using regression analysis to establish a linear relationship between the two variables – hours worked per week and yearly income. Hours per week Yearly Income ('000's) 18 43.8p 13 44.5 18 44.8 25.5 46.0 11.5 41.2 18 43.3 16 43.6 27 46.2 27.5 46.8 30.5 48.2 24.5 49.3 32.5 53.8 25 53.9 23.5 54.2 30.5 50.5 27.5 51.2 28 51.5 26 52.6 25.5 52.8 26.5 52.9 33 49.5 15 49.8 27.5 50.3 36 54.3 27 55.1 34.5 55.3 39 61.7 37 62.3 31.5 63.4 37 63.7 24.5 55.5 28 55.6 19 55.7 38.5 58.2 37.5 58.3 18.5 58.4 32 59.2 35 59.3 36 59.4 39 60.5 24.5 56.7 26 57.8 38 63.8 44.5 64.2 34.5 55.8 34.5 56.2 40 64.3 41.5 64.5 34.5 64.7 42.3 66.1 34.5 72.3 28 73.2 38…
A firm experienced the demand shown in the following table. Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w=0.9w=0.9 and w=0.3w=0.3). (Note: The exponential smoothing forecasts may be begun by assuming Yˆt + 1=YtY^t + 1=Yt.) Year Actual Demand Moving Average Exponential Smoothing (5-year) (3-year) (W = 0.9) (W = 0.3) 2000 800 2001 790 2002 785 2003 785 792 2004 790 787 2005 805 790 787 2006 825 791 794 2007 850 798 807 2008 825 811 827 2009 860 819 834 2010 * 833 846 The following table shows the square errors, (Yt−Yˆt - 1)2Yt−Y^t - 12, for forecasts from 2005 through 2009. Fill the table by calculating the root mean square error (RMSE) for each of the methods. Year Square…
Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two forecasting methods to see which method was better over this period. MONTH ACTUAL January 110 February 130 March 150 April 170 May 160 June 180 July 140 August 130 September 140 a. Forecast April through September using a three-month moving average. Note: Round your answers to 1 decimal place. b. Use simple exponential smoothing with an alpha of 0.3 to estimate April through September, using the average of January through March as the initial forecast for April. Note: Do not round intermediate calculations. Round your answers to 2 decimal places. c-1. Calculate MAD for each method. Note: Round your answers to 1 decimal place. c-2. Use MAD to decide which method produced the better forecast over the six-month period. multiple choice Exponential smoothing. Three-month moving average.
16) The following table shows daily offshore crude oil production by a country's national oil company, for 2008–2013. Year t (year since 2008) 0 1 2 3 4 5 Daily OffshoreProduction s(t) (million barrels) 2.35 2.21 2.07 2.00 2.00 2.00 (a) Use the data in the table to compute the average rate of change of s(t) over the period 2008–2013. __________million barrels/year Interpret the result. -During 2008–2013, daily imports from the country were decreasing. -During 2008–2013, daily imports from the country were constant. -During 2008–2013, daily imports from the country were increasing. (b) Which of the following is true? -From 2008 to 2013, the two-year average rate of change of offshore crude oil production for the country increased in value. -From 2008 to 2013, the two-year average rate of change of offshore crude oil production for the country decreased in value. - From 2008 to 2013, the two-year average rate of change of offshore crude oil production for the country…