Suppose actual quarterly sales (in thousands) for Year 5 are 193, 163, 207, and 105 respectively. Assuming there is no trend, forecast sales for the four quarters of Year 5. Use seasonal indexes (rounded to 4 decimal places) from Part A. Report forecast answers as integers accurate to the nearest thousand. Quarter 1 forecast = thousand Quarter 2 forecast = thousand Quarter 3 forecast = thousand Quarter 4 forecast = thousand Calculate the mean absolute percent error (MAPE) for the four forecasts. Use the integer forecast values you reported above. Report MAPE as percent accurate to 2 decimal places. Do not round intermediate values. МАРЕ 3D %
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- The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?The following table shows quarterly sales (in thousand units) for a product over 4 years. The overall sales average for the entire 4 years is 126.0625 (thousand units).Fill in the missing values assuming there is no trend.Round seasonal indexes to 4 decimal places.Report Averages accurate to at most 2 decimal places.Report Actual sales ('000) accurate to the nearest integer. Year 1 Year 2 Year 3 Year 4 Average Seasonal Index Quarter 1 92 93 95 106 Quarter 2 105 106 105 101 Quarter 3 197 187 196 1.5211 Quarter 4 106 116 121 0.8865 PART BSuppose actual quarterly sales (in thousands) for Year 5 are 93, 123, 206, and 126 respectively. Assuming there is no trend, forecast sales for the four quarters of Year 5.Use seasonal indexes (rounded to 4 decimal places) from Part A.Report forecast answers as integers accurate to the nearest thousand.Quarter 1 forecast = thousandQuarter 2 forecast = thousandQuarter 3 forecast = thousandQuarter 4 forecast =…Year Season Sales 2018 Winter 40 2018 Spring 29 2018 Summer 31 2018 Fall 40 2019 Winter 102 2019 Spring 87 2019 Summer 96 2019 Fall 132 2020 Winter 105 2020 Spring 93 2020 Summer 105 2020 Fall 117 2021 Winter 141 2021 Spring 39 2021 Summer 114 2021 Fall 123 What is the slope of the trend equation obtained by linear regression? Round to two decimal digits. What is the intercept of the trend equation obtained by linear regression? Round to two decimal digits. What is the seasonal index for Spring? Round to two decimal digits. The quarter number for Winter of 2018 is 1. What is the quarter number for Spring of 2025? What is the trend based forecast for Spring of 2025. Round to a whole number. What is the seasonally adjusted trend based forecast for Spring of 2025? Please do not use excel to find the slope and intercept, thank you so much!
- The 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 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 1 215 2 240 3 205 4 190 5 160 6 195 7 150 8 140 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to 1 decimal place.The 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 QUARTER SALES 1. 211 5 155 235 6 198 3 206 7 154 4 190 8 142 Use regression and seasonal indexes to forecast quarterly sales for the next year. (Do n ot round intermediate calculations. Round your answers to the nearest whole number.) Answer is complete but not entirely correct. Quarter Forecast 142 8 157 8 121 8 10 11 12 103
- The table below shows the sales for a plastics manufacturer recorded over the past year. The seasonal indexes for each quarter are also provided). To track the trend for these four quarters, use the indexes to deseasonalize the sales data. Quarter 1 Sales 738 Index 75.0 Deseasonalized Sales 234 1012 104.0 1196 121.0 962 100.0 What are deseasonalized sales for quarter 2? 973.1 1052.5 1291.5 1012.0 1027.7Year Quarter Sales Isolated trend 2016 1 18 2016 2 28 2016 12 2016 4 8 2017 1 16 2017 2 38 2017 3 24 2017 4 17 2018 1 34 A 2018 2 40 2018 29 2018 4 26 2019 1 42 2019 2 52 2019 40 2019 4 34 43.75 2020 1 46 2020 2 58 The table contains decomposition figures of the quarterly sales in millions of Rands for a large store. The value of A isThe following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LO
- The following table shows a tool and die company's quarterly sales for the current year. What sales would you predict for the first quarter of next year? Quarter relatives are SR= .94, SR,- 97, SR= 97, and SR, 112. For the trend forecast (T), add the difference between quarter 3 and quarter 4's deseasonalized sales data to the deseasonalized quarter 4 sales. (Round your answer to 1 decimal place.) Quarter Sales 84.6 83.0 84.7 108.0The long-term financial forecast plays a crucial part in the company's long-term strategic plan. True or False True False 25 28 étv N 4The 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 1 2 5678AWN 3 4 8 SALES 219 237 208 171 169 Quarter 9 10 11 12 192 157 132 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast