From the following annual data of sales (in 000 .$.) Find the trend values by using least square method. Also estimate the sales of 2014.
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Q: Period 1 2 3 4 6. 7 8 9 10 11 12 Sales 568 604 645 742 661 606 749 680 704 736 660 756
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Q: a) Forecasted sales for year 6 using a 3-year moving average is sales (round your response to one…
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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 Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
- Management of a home appliance store wants to understand the growth pattern of the monthly sales of a new technology device over the past two years. The managers have recorded the relevant data in the file P13_05.xlsx. Have the sales of this device been growing linearly over the past 24 months? By examining the results of a linear trend line, explain why or why not.Use the sales data given below to determine: (a) the least squares trend line, and (b) the predicted value for 2003 sales. Year Sales (Units) 1996 100 1997 110 1998 122 1999 130 2000 139 2001 152 2002 164 To minimize computations, transform the value of x (time) to simpler numbers. In this case, designate year 1996 as year 1, 1997 as year 2, etc.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 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.Cell phone sales for a California-based firm over the last 10 weeks are shown in the following table. Plot the data, and visually check to see if a linear trend line would be appropriate.Then determine the equation of the trend line, and predict sales for weeks 11 and 12.Week Unit Sales1 7002 7243 7204 7285 7406 7427 7588 7509 77010 775The 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 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. ForecastPlease answer parts i, ii and iii of the below question. The table below shows the sales figures for a brand of shoe over the last 12 months. Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 Using the following, forecast the sales for the months up to January the following year:- i) A simple three month moving average. ii) A three period weighted moving average using weights of 1, 2 and 3. Assign the highest weight to the most recent data. iii) Exponential Smoothing when α= .6 and the forecast for March is 350.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 1027.7