Two different forecasting techniques (F1 and F2) were used to forecast demand for cases of bottled water. Actual demand and the two sets of forecasts are as follows: TTTT PREDICTED DEMAND Period Demand F1 F2 1 68 63 66 2 75 70 67 70 75 70 74 69 72 69 70 73 72 68 75 80 70 77 78 74 84 Click here for the Excel Data File a. Compute MAD for each set of forecasts. Given your results, which forecast appears to be more accurate? (Round your answers to 2 decimal places.) MAD F1 MAD F2
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4In the packaging department of a large aircraft parts distributor, a fairly reliable estimate ofpackaging and processing costs can be determined by knowing the weight of an order. Thus, theweight is a cost driver that accounts for a sizable fraction of the packaging and processing costsat this company. Data for the past 10 orders are given as follows:Because of high tuition costs at state and private universities, enrollments atcommunity colleges have increased dramatically in recent years. The following data show theenrollment (in thousands) for Jefferson Community College from 2001–2009:Year Period (t) Enrollment (1000s)2001 1 6.52002 2 8.12003 3 8.42004 4 10.22005 5 12.52006 6 13.32007 7 13.72008 8 17.22009 9 18.1Compute F10: the Forecast for 2010. Compute Pearson’s Correlation Coefficient Use the Method of Least Squares to obtain the Best-Fit-Line for this data. Use the line to compute the forecast.
- The demand and forecast information for the XYZ Company over a twelve-month period has been collected in the Microsoft Excel Online file below. Use the Microsoft Excel Online file below to develop forecast accuracy and answer the following questions. Forecast Accuracy Measures Period Actual Demand Forecast Error Absolute Error Error^2 Abs. % Error 1 1,300 1,378 2 2,000 1,676 3 1,800 1,974 4 1,700 2,272 5 2,300 2,570 6 3,800 2,868 7 3,200 3,166 8 3,100 3,464 9 3,900 3,761 10 4,600 4,059 11 4,200 4,357 12 4,300 4,655 Total Average RSFE MAD MSE MAPE Tracking Signal 1. What can be concluded about the quality of the forecasts? Assume that the control limit for the tracking signal is ±3. The results indicate (bias or no bias) in the…Toward the middle of the harvesting season, peaches for canning come in three types, early, late, and extra late, depending on the expected date of ripening. During a certain week, the data to the right were recorded at a fruit delivery station. Complete parts (a) through (d) below. 40 trucks went out carrying early peaches; 71 carried late peaches; 52 carried extra late peaches; 26 carried early and late; 32 carried late and extra late; 11 carried early and extra late; 6 carried all three; 5 carried only figs (no peaches at all). a) How many trucks carried only late variety peaches? trucks (Type a whole number.) (b) How many carried only extra late? trucks (Type a whole number.) (c) How many carried only one type of peach? trucks (Type a whole number.) (d)How many trucks (in all) went out during the week? trucks (Type a whole number.)Toward the middle of the harvesting season, peaches for canning come in three types, early, late, and extra late, depending on the expected date of ripening. During a certain week, the data to the right were recorded at a fruit delivery station. Complete parts (a) through (d) below. 40 trucks went out carrying early peaches; 76 carried late peaches; 64 carried extra late peaches; 31 carried early and late; 34 carried late and extra late; 13 carried early and extra late; 6 carried all three; 8 carried only figs (no peaches at all). a. How many trucks carried only late variety peaches? b. How many carried only extra late? c. How many carried only one type of peach? d. How many trucks (in all) went out during the week? Thank you so much
- IOG Technologies offers semiconductor and system solutions for automotive industrial and multimarket sectors for applications in communication. The following data relates to the production of three products manufactured by them: Product Price (RM) Quantity 2000 2016 2000 2016 BD-1005 3.00 3.20 60 80 LCM-2134 2.00 2.50 100 90 DDK-456 3.50 4.00 500 700 Determine the Laspeyres Price Index (LPI) and Paasche Price Index (PPI) for 2016 using 2000 as the base period.The following are data on the percent effectiveness of a pain reliever and the amounts of three different medi-cations (in milligrams) present in each capsule: PercentMedication A Medication B Medication C effectivex1 x2 x3 y15 20 10 4715 20 20 5415 30 10 5815 30 20 6630 20 10 5930 20 20 6730 30 10 7130 30 20 8345 20 10 7245 20 20 8245 30 10 8545 30 20 94Assuming that the regression is linear, estimate theregression coefficients after suitably coding each of thex’s, and express the estimated regression equation interms of the original variables.The management of BCD Inc. would like to separate the fixed and variable components of electricity as measured against machine hours in one of its plants. Data collected over the most recent six months follow:Electricity MachineMonth Cost Hours January $1,100 4,500February 1,110 4,700March 1,050 4,100April 1,200 5,000May 1,060 4,000June 1,120 4,600Required: 1. Using the method of least squares, compute the fixed cost and the variable cost rate for electricity expense. (Round estimates to the nearest cent.) 2. Compute coefficients of correlation and determination
- Could you please teel me why should a firm, for profit, care not only about the expected profit, but also about the variance of the profit.thanksABC Company has decided to use 20 test markets to examine the sensitivity of demand for its new product, Hand Sanitizer, to various prices, as shown in the following table. Each market had approximately the same level of business activity and population. Test Market Quantity sold (Thousands of Pens) Price Charged (cent) 1 20 50 2 21 50 3 19 55 4 18 60 5 20 60 6 14 65 7 16 65 8 20 70 9 12 70 10 14 80 11 12 70 12 10 70 13 14 65 14 16 90 15 18 45 16 16 70 17 20 65 18 12 80 19 18 70 20 10 50 Q.1. Using a linear regression model, estimate the demand function for ABC Company’s new product, Hand sanitizer. Q.2. Interpret the coefficient value of the independent variable of the estimated demand function. Q.3. What will be the predicted/estimated sale for each price shown in column 2? Q.4. Find the prediction interval at…Amex PLC has gathered following information on the sales of face mask from April 2020 toSeptember 2020.Month Sales ($)April 17,000May 18,000June 19,500July 22,000August 21,000September 23,000You are required to;b. Calculate the forecasted sales difference if you use 3-period weighted moving averagedesigned with the following weights: July 0.2, August 0.3 and September 0.5.