anth Sales Forecast 1 Forecast 2 1 770 771 769 2 789 785 787 3 794 790 792 780 784 798 768 770 774 772 768 770 7 760 761 759 775 771 775 786 784 788 790 788 788 Compute the MSE and MAD for each forecast. Does either forecast seem superior? Explain. - Compute MAPE for each forecast.
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- Plot the logarithm of arrivals for each transportation mode against time, all on the same graph. Which now appears to be growing the fastest?Time Actual (Y) Forecast (Yhat) Forecast Error 100 1 2 110 3 115 4 120 If naïve method is used for the above data, what is the error for period 4, e(4)? Hint: You have to calculate he forecasted value before you can calculate the forecast error. 10 15 can not be determinedThe demand of a product of a company is given below for the periods. Can we use Winter method for forecasting demands of the A following 3 periods? Why? If yes, apply it past 4. 6. Demand 27 31 40 31 35 45
- 2. Montyboy Pet Shop ships boxed can dogfood anywhere in the country. Using the following information, forecast the shipments for the first four months. Seasonal Relative Month January February March 1.2 1.3 1.3 1.1 0.8 0.7 The monthly forecast equation being used is: Yt = 402 + 3t April May June Where: to = January last year Yt = number of shipments Month July August September October November December Seasonal Relative 0.8 0.6 0.7 1.0 1.1 1.4 Question: Determine the trend amounts for the first four months of the next year assuming January, t=24; February, t=25; etc. Note: Round answers to whole numbers.Historical demand for Peeps is as displayed in the table. Month Demand January 11 February 18 March 31 April 39 May 44 June 53 July 67 August 82 September 96 Develop forecasts from June through October using these techniques: Holt's method with alpha=0.2 and beta=0.1. For Holt's model, the level and trend for May are assumed to be 44 and 12. Judge which forecast method is the best based on MAD.Define Forecasts and forecast errors in time series anaylsis?
- A company that produces video equipment, including videocameras and televisions, is attempting to forecast what newproducts and product innovations might be technologicallyfeasible and that customers might demand 10 years into thefuture. Speculate on what type of qualitative methods itmight use to develop this type of forecast.Actual sales of TV's for the first six month in 2021 were as follows:January 60 February 80 March 42April 68 May 44 June 72 Use this information and determine in whole numbers: 1 The average actual monthly sales for that period 2 Trends: Reduce this average by 6% per month for the next three months 3 Simple Moving Average (SMA): make a forecast for July using a three months simple movingaverage. 4 Weighted Moving Average (WMA): make forecast for July, using a three months weightedmoving average where the weights are 0.5; 0.3 and 0.2 respectively.OA linear regression model is Units 3,414-0.839xWeek. For week 45, what is the forecast for the number of units? Round your answer to the nearest whole number. OO units
- Paw Patrol Inc. manufactures toys for kids from 1 to 10 years old. The summary of toy sales by month in 2017 and 2018 is as follows: Dt April May 2018 18600 Period Demand 18716 June 19235 2017 September 19400 July August 19500 October 18300 19753 November 17200 September 18320 December 14998 October 17652 2018 January February March 19800 November 16200 19555 December 15563 19800 What is the Mean Absolute Deviation (MAD), when using the weighted 4-period moving average technique? Use weights of 0.6, 0.2, 0.1, and 0.1 for the most recent period, the second most recent period, the third most recent period, and the fourth most recent period, respectively. O 5445 O 1256 O 1555 O 4450 O 1140Director Very Busy needs to allocate time this week for office appointments, so he needs to forecast the number of employees who will seek appointments. The director has gathered the following time series data recently Period Employee Appointments 4 weeks ago 95 3 weeks ago 80 2 week ago 65 last week 50I Consider the demand for trading cards listed below. Month Demand Jan. 51,000 48,000 Feb. March 55,000 April May 58,000 66,000 June 69,000 80,000 July Aug. 95,000 Use Excel to prepare a forecast for September, October, and November using linear regression Print out the sheet of results, as well as a sheet containing the formulas that you used ( can be used to toggle between displaying values and displaying formulas or you can click on Formulas>Formula Auditing→Show Formulas.) and for the cars is 16.000