5 6 7 8 Demands 700 685 648 717 713 728 754 7
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Develop an adjusted exponential forecast for a firm with the demand for bread as shown in the table below.
| week | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| Demands | 700 | 685 | 648 | 717 | 713 | 728 | 754 | 762 |
Let α = 0.1 and β = 0.2. Previous average of Ft–1= 650, and let the initial trend adjustment, Tt–1 = 0?
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- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?The US. import of wine (in hectoliters) for several years is given in Table 5. Determine whether the trend appearslinear. Ifso, and assuming the trend continues, in what year will imports exceed 12,000 hectoliters?Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
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- Can the average rate of change of a function be constant?lakhs) of a certain commodity for the year On the basis of quarterly sales (in 2008-12, the following calculations were made : Trend: Y = 20 + 0.5 t with origin at 1st quarter of 2008. where 1 = time unit = one quarter and y = quarterly sales ( Seasonal variations: Quarter I II III IV Seasonal Index 80 90 120 110 Estimate the quarterly sale for the year 1979 using multiplicative model.The forecast with out seasonality is modeled as: Sales = 6 * t + 236.00, where t= time in months, beginning in January 2015. Seasonality for the first three months are given in the table below. Determine a seasonalized forecast for Feb of 2016. Month Seasonal Factor January 1.9000 February 0.6262 March 0.1000 Submit Answer format: Number: Round to: 1 decimal places. What value with the season index that is created for the 12 months of the year add up to? Submit Answer format: Number: Round to: 0 decimal places.
- Monthly sales have been found to follow a linear trend of y = 10 + 8x, where y is the number of items sold and x is the number of the month. Monthly deviations from the trend have been calculated and follow an additive model. In month 12, the seasonal variation is estimated to be -6. What is the forecasted number of items to be sold in month 12?X 3.29 The quarterly revenues of a small medical supply company for the last several years (27 quarters) were plotted and seen to have a roughly linear trend component. The information below was computed for y₁. Y₂..... Y27 using one of the company's spreadsheet computer programs. t=1,2,..., 27 y, quarterly gross revenues ($10,000) Σ y = 7,146 3ty w 113,615 SS-120,640 a. Using the method of least squares, fit a linear trend model to the revenue data. b. Test for significance of the trend component assuming indepen- dent, normally distributed error terms. c. Forecast revenues for t= 28 and t = 29 using the model fit in part (a). d. Construct 95% prediction intervals for y28 and Y29- e. Construct 90% prediction intervals for y2a and Y20Ten years of monthly data of a seasonally adjusted series are used to estimate a linear trend model as T = 24.10+ 0.32t. In addition, seasonal indices for January and February are calculated as 1.08 and 0.97, respectively. Make a forecast for the first two months of next year. (Do not round intermediate calculations. Round your answers to 2 decimal places.) ýt January February
