National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows: Sales Month (000) Units Feb. Mar. Apr. May. Jun. Jul. Aug. 15 18 12 20 23 23 27 Click here for the Excel Data File forocos Contombor u lumo ucin gach of the
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- gnment 1.d X ment%202.pdf .xlsx HP Work & Supply Chain Marakane Sales JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Total - 1 / 2 - Question 1 The monthly demand of a company is showed below, please use the static method to forecast the demand for Year 6. Year 1 Q Search 2,000 3,000 3,000 3,000 4,000 6,000 7,000 6,000 10,000 12,000 14,000 8,000 78,000 Catherine Caramp....pdf Z Year 2 140% 3,000 4,000 3,000 5,000 5,000 8,000 3,000 8,000 12,000 12,000 16,000 10,000 89,000 LDE + @ I Assignment 2 Year 3 Question 2 Historical demand for Peeps is as displayed in the table. 2,000 5,000 5,000 3,000 4,000 6,000 7,000 10,000 15,000 15,000 18,000 8,000 98,000 T2202- 2022.pdf 0 Year 4 }}) 5,000 4,000 4,000 2,000 5,000 7,000 10,000 14,000 16,000 16,000 20,000 12,000 115,000 ! Year 5 5,000 2,000 3,000 2,000 7,000 6,000 8,000 10,000 20,000 20,000 22,000 8,000 113,000 Q☆ l EN USPlease do not give solution in image formate thanku. Bradley's Copiers sells and repairs photocopy machines. The manager needs weekly forecasts of service calls so that he can schedule service personnel. Use the actual demand in the first period for the forecast for the first week so error measurement begins in the second week. The manager uses exponential smoothing with α = 0.5 Forecast the number of calls for week 6, which is next week. WEEK ACTUAL SERVICE CALLS 1 28 2 32 3 40 4 27 5 30The data shown are quarterly revenues (in Sthousands) from Roget's Books from 2013-Q1 through 2020-Q2. 6. Quarter 2013-1 2013-2 2013-3 2013-4 2014-1 2014-2 2014-3 2014-4 2015-1 2015-2 2015-3 2015-4 2016-1 2016-2 2016-3 2016-4 2017-1 2017-2 2017-3 2017-4 Revenue 2372 2740 2518 4708 2392 Quarter 2018-1 2018-2 2018-3 2018-4 2019-1 2019-2 2019-3 2019-4 2020-1 2020-2 Revenue 2725 2924 3118 5112 2777 2949 1:27:04 2811 2685 4795 2812 2893 2848 4894 2687 2903 2674 4871 2844 2933 3237 5350 3035 3028 2791 5252 Click here for the Excel Data File, Data file should open in a new browswer window. Select "File" then "Save As" to download the file to your computer and be able to use it in Excel. a. Determine the regression equation. Regression equation: ŷ = | (Round to 1 decimal places.) b. Determine the specific index for each quarter places.) dexes should be in decimal form (e.g. 1.36 not 136). Rounded to 2 decimal Quarter Quarterly Index Q1 Q2 Q3 Q4 c. What are the estimated sales (forecast) for…
- 1. Favors Distribution Company purchases small imported trinkets in bulk, packages them, and sells them to retail stores. They are conducting an inventory control study of all their items. The following data for the year 2006 are for one such item, which is not seasonal. [10 Points] Month Sales Jan Feb 18 19 Mar Apr May Jun 17 21 20 19 Jul 20 Aug 23 a. Use trend projection to estimate the relationship between time and sales (state the trend line equation in this problem). b. Calculate forecasts for February 2007, April 2007, and February 2008(4) The Great Northwest Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the holiday season and during the spring. It has accumulated the following data for orders per season (quarter) during the past five years. Orders (1,000s) Year 1 Year 2 Year 3 Year 4 Year 5 Winter (Q 1) Spring (Q 2) Summer (Q 3) 18.6 18.1 22.4 23.2 24.5 23.5 24.7 28.8 27.6 31.0 20.4 19.5 21.0 24.4 23.7 Fall (Q 4) Total 41.9 46.3 45.5 47.1 52.8 104.4 108.6 117.7 122.3 132.0 Develop a seasonally adjusted forecast model for these order data. Forecast demand for each quarter for year 6, using the annual trend line as given: Y(t) = 96.33 + 6.89t (a) Find seasonal index for each quarter (b) Find seasonally adjusted demand forecast for each quarter for year 6 (c) Find MAD for seasonally adjusted forecasting for year 1 through 5.9. Mancini's Pizzeria sells four types of pizza crust. Last week, the owner tracked the number sold of each type, and this is what she found. Type of Crust Number Sold Thin crust 344 Thick crust 240 Stuffed crust 175 Pan style 316 Based on this information, of the next 5000 pizzas she sells, how many should she expect to be thin crust? Round your answer to the nearest whole number. Do not round any intermediate calculations.
- Given the demand data, answer the following questions below. Year Sales 1 - 123 2 - 118 3 - 109 4 - 112 5 -100 6 -110 7 -124 8 - ? What will be the forecast demand in Year 8 using Naïve method?a.) 120b.) 110c.) 115d.) 124ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using the naive approach.The Outdoor Company is a catalog sales operation that specializes in outdoor recreational clothing. Demand for its items is very seasonal, peaking during the Christmas season and during the spring. It has accumulated the following data for orders per season (quarter) during the past 5 years: Quarter Jan-Mar Apr - Jun Jul - Sep Oct-Dec 1 22.60 28.50 24.40 43.90 2 19.10 29.70 23.50 47.30 Orders (1,000s)/Year 3 26.40 32.80 24.00 47.50 a. Calculate the overall average demad. 4 25.20 28.60 26.40 49.10 5 28.50 34.00 27.70 55.80 Average Demad per Quarter b. Calculate the average demad per quarter in the space given in the above table. c. Calculate the seasonal index in the space given in the above table. Seasonal Index
- Year Sales 1) 123 2)118 3) 109 4) 112 5) 100 6) 110 7) 124 8)Determine the demand in Year 8 using a 3-month moving average using the sales table. Use weights of 0.40, 0.30 and 0.30The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER SALES 154 190 154 145 216 236 208 175 Use time series decomposition to forecast quarterly sales for the next year. (Do not round intermediate calculations. Round your answers to the nearest whole number.) Quarter Forecest 19 10 11 12The monthly demand for units manufactured by the Acme Rocket Company has been as follows:Month Units Month UnitsMay 100 September 105June 80 October 110July 110 November 125August 115 December 120a. Use the exponential smoothing method to forecast the number of units for June to January. Theinitial forecast for May was 105 units; a = 0.2.b. Calculate the absolute percentage error for each month from June through December and theMAD and MAPE of forecast error as of the end of December.c. Calculate the tracking signal as of the end of December. What can you say about the performanceof your forecasting method?