Suppose a firm has had the following historic sales figures. Year: 2016 2017 2018 2019 Sales $3,400,000 $4,650,000 $3,300,000 $2,900,000 What would be the forecast for next year's sales using the naïve approach? Answer is complete but not entirely correct. Next year's sales $ 3,550,000 2020 $3,500,000
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- 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.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 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 84.7 108.0My App is a small but growing start-up that sees demand for several of its apps increasing quickly. The table below shows the last six months of downloads. Use a forecast for the first month of 220,000, an initial trend forecast of 35,000, and smoothing parameters of 015 for both demand smoothing and trend smoothing Month (t) Monthly Application Downloads Forecast for Next Month Trend 220,000.00 35,000.00 200,000 2 250, 100 334,000 380,000 440,000 500,000 (Round your answers to 2 decimal places.) Complete the table above, filling in the "Forecast for next month" and "Trend" columns, using double a. exponential smoothing (Round your answers to 2 decimal places.) Month 7's forecast is b.Sales over the past 10 years are shown below. Using the method of least squares, calculate the values of a and b to complete this regression equation. Year Sales 1 1770 2 1880 3 1070 4 1420 5 1540 6 2000 7 1910 8 1360 9 1400 10 1500 (Indicate a negative answer using a "-" sign. Do not round intermediate calculations and round your final answer to 3 decimal places.) What is your forecast for next year’s sales? (Do not round intermediate calculations and round your final answer to 2 decimal places.)
- Sales of a particular product (in the thousands of dollars) for the year of 2015 through 2018 have been $48,000, $64,000, $67,000 and $83,000 respectively. (a) What sales would you predict for 2019, using a simple four year moving average? (b) What sales would you predict for 2019, using a weighted moving average with weights of 0.50 for the immediate preceding year 0.3, 0.15, and 0.05 for the three years before that?Make a 15-year simple linear regression forecast. Example: Railroad Products Co. RPC Sales Car Loadings Year ($millions) (millions) 1 9.5 120 2 11.0 135 3 12.0 130 4 12.5 150 5 14.0 170 6 16.0 190 7 18.0 220An electronic appliance manufacturer wants to know if there is a relationship between percentage change in deposable personal income which is reported quarterly by the government, and the percentage change in appliances sold by the manufacturer following same years of quarterly data. Brenda Chee and Clarence Paulus lead an analyst team has obtained data for the past 10 quarters. Table 3 Quarter Percent change in income Percent Change in appliance sold Quarter Percent change in income Percent Change in appliance sold 1 -2.3 -2.5 6 -1.0 1.0 2 -1.5 -1.0 7 0.7 1.4 3 2.8 7.4 8 5.2 3.4 4 0.5 2.6 9 -2.5 -0.5 5 4.6 8.5 10 1.7 1.8 1) What forecasting model should be used for this data.Why? 2) Develop the forecasting model that you have proposed in(a). 3) Compute the relationship for these data. In your opinion, is the relationship between independent variable strong enough to base a predictive the…
- An electronic appliance manufacturer wants to know if there is a relationship between percentage change in deposable personal income which is reported quarterly by the government, and the percentage change in appliances sold by the manufacturer following same years of quarterly data. Brenda Chee and Clarence Paulus lead an analyst team has obtained data for the past 10 quarters. (Hint: Provides your answers in two decimal points) (a) What forecasting model should be used for this data. Why? (b) Develop the forecasting model that you have proposed in (a). (c) Compute the relationship for these data. In your opinion, is the relationship between independent variable strong enough to base a predictive the dependent variable? Explain your answer.A manufacturer of printed circuit boards uses exponentialsmoothing with trend to forecast monthly demand of its product.At the end of December, the company wishes to forecast salesfor January. Th e estimate of trend through November has been200 additional boards sold per month. Average sales have beenaround 1000 units per month. Th e demand for December was1100 units. Th e company uses a 0.20 and b 0.10. Make aforecast including trend for the month of JanuaryA manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives areSR1 = .90, SR2 = .95, SR3 = 1.05, and SR4 = 1.10. The trend equation is: Ft= 10 + 5t. Over thepast nine quarters, demand has been as follows:Period, t 1 2 3 4 5 6 7 8 9Demand 14 20 24 31 31 37 43 48 52Is the forecast performing adequately? Explain.