Demand history for the past three years is shown below. Year Quarter Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Demand 185 217 Year 1 310 251 194 196 Year 2 320 301 189 207 Year 3 330 256 Round your answer to three decimal places. What is the seasonal index for Q1?
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- (b) Demand history of five different products of a company is shown below. Products 2012 2013 2014 2015 2016 2017 2018 2019 2020 A 37 40 41 45 49 26 34 30 26 23 33 28 32 C 58 55 32 38 45 56 62 70 77 86 95 83 88 81 92 85 i. Name the methods that is suitable to forecast the demand of the above five products? ii. Forecast demand of the product B or D with error for the year 2021. If you need a value of a then consider it 0.7.Assuming the following deseasonalized demand, what would your Level and Trend FORECAST factors be for future deseasonalized demand estimates? (Hint, you might want to use excel for this) period 1 2 3 4 5 6 7 8 9 10 13673 6640 2737 3486 141 13186) 5448 3485 7728 16591 8236 3316 855358 11 12 13 15 16 17 18 19 Demand Deseasonalized D₁ Demand D 3200 7658 4420 2384 3654 8680 5795 1953 4742 20 4472 4657 4956 5074 5157 5917 6646 6850 6791 6573 6363 6308 6932 7887 8662 8989 O Level-4696 Trend-343 O Level-3612. Trend-264 O Level 3629; Trend-263 O Level-2528: Trend-185The following are historical demand data: YEAR SEASON ACTUALDEMAND 2011 Spring 203 Summer 144 Fall 382 Winter 565 2012 Spring 471 Summer 271 Fall 686 Winter 955 Use regression analysis on deseasonalized demand to forecast demand in summer 2013. (Do not round intermediate calculations. Round your answer to the nearest whole number.)
- The K&R Camera shop sells all the latest cameras and accessories. To meet customer demand, the manager must forecast demand for items she sells. Lately the XR-42S zoom lens has been very popular. Recent monthly demand for this item has been as shown: Number of Lenses Month Sold 1 12 17 2 3 4 15 20 18 23 6.Use regression analysis on deseasonalized demand to forecast demand in Summer of Year 3, given the following historical demand data: Year Season Actual Demand 1 Spring 205 Summer 140 Fall 375 Winter 575 2 Spring 475 Summer 275 Fall 685 Winter 965Find the MAD and Tracking signal in below table. Do you think this forecast is acceptable? Why? How many units this company shall keep as the safety stocks if service level is 90%? Period Actual Demand Forecast 220 200 2 300 310 3 400 340 4 340 350 5 280 300 250 270
- The following are historical demand data: ACTUAL YEAR SEASON DEMAND 2 years ago Spring Summer 205 151 Fall 379 Winter Spring Summer 560 last year 481 268 679 959 Fall Winter Use regression analysis on deseasonalized demand to forecast next summer's demand. (Round your answer to the nearest whole number.) Forecast for next summer's demandGiven the following history, use a three-quarter moving average to forecast the demand for the third quarter of this year. Note that the 1st quarter is Jan, Feb, and Mar; 2nd quarter Apr, May, Jun; 3rd quarter Jul, Aug, Sep; and 4th quarter Oct, Nov, Dec. (Round final answer to a whole number.) JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Last year 165 185 200 230 240 265 210 200 195 265 290 315 This year 175 200 165 260 260 200 Forecast for the third quarterPrepare a Demand Forecast for “Year 5” using Excel. Quarterly Data for Cars Sales Yt Year Quarter Sales (1000s) Year 1 1 4.80 2 4.10 3 6.00 4 6.50 Year 2 1 5.80 2 5.20 3 6.80 4 7.40 Year 3 1 6.00 2 5.60 3 7.50 4 7.80 Year 4 1 6.30 2 5.90 3 8.00 4 8.40 Year 5 1 2 3 4
- Month Demand Forecast Error Abs Error alpha 1 20 2 18 3 21 4 25 5 24 6 27 7 22 8 30 9 23 10 20 11 29 12 22 Mean Bias MAD (mean error) Problem 6: Maverick Jeans' demand manager decided to evaluate exponential smoothing. To maintain com- parability, she used the data from problem 6, copied below. 1 Month 2 3 Demand 20 18 21 25 4 5 24 6 7 8 9 10 11 12 27 22 30 23 20 29 22 Develop forecasts for months 5-12. Calculate the Bias and MAD. Use a starting forecast of 20 for month 4 and an alpha value of 0.2. (Note: Adjust all cell values to two decimal points.)Given the following history, use a three-quarter moving average to forecast the demandfor the third quarter of this year. Note that the 1st quarter is Jan, Feb, and Mar; 2ndquarter Apr, May, Jun; 3rd quarter Jul, Aug, Sep; and 4th quarter Oct, Nov, JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DECLast year 120 140 145 195 205 220 165 155 145 220 245 265This year 140 145 200 210 240 255The 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…