Next Stândard Period Error Forecasting Method Used Forecast (MSE) 1.3-period UnWMA 10.42 3.24 2.4-period UnWMA 3.3-period WMA 10.38 3.51 10.83 3.03 4. Simple Exponential Smoothing 5. Trend Projection 8.24 5.04 11.43 1.16
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- 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 unitsUse simple exponential smoothing with a = 0.6 to forecast the tire sales for September through December. Assume that the forecast for August was for 46 sets of tires. Do your forecasts seem to be biased? Why or why not? Month Sales August 53 September35 October 48 November 40Use simple exponential smoothing with a = 0.3 to forecast bike sales for September through December. Assume that the forecast for September was 60 units. a) What will be the forecast for December? b) Calculate the MAD. Last saved 11:13:58 AM budy Questions Filter (25) Month September October November December F3 X C O Search P Bike Sales 54 72 60 ? Y
- Sales in a company are $188 million in 2009 and increase $208 million in 2010. Compute the percentage increase in sales using the usual formula Compare this value to the approximation The approximation performs (1) percentage change increases. 100 x (1) O better (2) O deteriorates O worst O improves 100 x 100 x (Sales 2010 - Sales 2009) Sales 2009 100 x [In (Sales2010) -In (Sales2009)] (Sales 2010 - Sales2009) Sales 2009 100 x [In (Sales 2010) -In (Sales2009)] = [ (Express your response as a percentage and round to three places) Now, assume that sales in a company are $188 million in 2009 and increase $264 million in 2010. = (Sales2010 - Sales 2009) Sales 2009 % % % 100 x [In (Sales 2010) -In (Sales 2009)] = [ (Express your response as a percentage and round to three places) % when the change is small. The quality of the approximation (2). as theConsider the following time series. 1 2 4 Y, 6 11 9 14 15 a. Choose the correct time series plot. (i) 16 (ii) 16 14 14 12 12 10 10 8 6. 6. 4 4 2 1 Time Period (t) Time Period (t) Time Period () Time Period (t) (iii) 16 (iv) 16 14 14 12 12 10 10 8 1 Time Period (t) Time Period (t) Time Series Value Time Series Value Time Series Value Time Series ValueUse General Linear Proce ss to determine the Emean functon and ARC2) given the autocovariance function of ky XE 七ート 2ヒー2
- (Ch7) If the mean time between in-flight aircraft engine shutdowns is 12,500 operating hours, what is the 90 percentile on the distribution of the number of hours until the next shutdown? (hint: convert the mean time between events to the mean events per hour λ, then apply inverse exponential) Question 7Select one: a. 20,180 hours b. 18,724 hours c. 23,733 hours d. 28,782 hoursThe 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 45Paw 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 1140
- A certain standardized test measures students' knowledge in English and math. The English and math scores for 10 randomly selected students were recorded and analyzed. The results are shown in the computer output. Predictor Coef SE Coef t-ratio Constant -124.13 78.712 0.046 Math 1.223 0.1966 6.220 0.000 S = 34.55 R-Sq = 82.8% R-Sq (Adj) = 83.5% Which of the following represents the standard deviation of the residuals? O 1.223 34.55 78.712 124.13Director 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 50Question 3 The number of tons of brake assemblies received at an auto parts distribution center last month was 625. The forecast tonnage was 650 for last month. The company uses a simple exponential smoothing model with a smoothing constant of 0.46 to develop its forecasts. What will be the company's forecast for the next month? Add your answer