Medium-term forecasts are used for making medium-term decisions related to planning for new products, capital expenditures, facility location or expansion, and research and development.
Q: Sales of tablet computers at Marika Gonzalez's electronics store in Washington, D.C., over the past…
A: Ans)
Q: The following data are for calculator sales in units at anelectronics store over the past 9 weeks:…
A:
Q: Week 1 2 3 4 5 6 Value 19 14 16 11 18 14 . Construct a time series plot. Time Series Value 20 F10 4…
A: 1) plot 1 horizontal b) Time period Actual Value(A) Moving avg. Forecast(F) Forecast error…
Q: Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value…
A: The answer is as below:
Q: It has been said that forecasting using exponential smoothing is like driving a car by looking in…
A: As there are multiple questions posted, as per policy will answer the first question only. If you…
Q: Forecasts affect planning but not the other management functions.
A: This do not require any introduction
Q: What type of analytics seeks to recognize what is going on as well as the likely forecast and make…
A: Analytics which involves predictions based on historical and current data is known as predictive…
Q: The data below represents the quarterly changes in demand for a product over the next 3 months.…
A: Given data is
Q: Let’s say you work for a company that makes prepared breakfast cereals like corn flakes. Your…
A: There are two different forecast techniques used by the companies, which are quantitative and…
Q: If a forecast can be made using a quantitative model, a forecaster need not use her personal opinion…
A: This do not require any introduction
Q: Forecast accuracy is important because it impacts the organizations' money and people. True False
A: Accurate forecasting helps with cost cutting, production and staff scheduling, capital planning and…
Q: Given that the previous forecast of 65 turnedout to be four units less than the actual demand; the…
A: In simple exponential smoothing method, forecast for period t can be calculated using the following…
Q: A production company was able to hit the following sales order for the past 3 months: 45% of 420pcs…
A: Given data is
Q: Jane is trying to forecast demand for her store, using moving average with n=2, Fill in the missing…
A: Find the given details below: Given details: Year Quarter Enrollment 1997 1 313 2 285…
Q: Sales of tablet computers at Marika Gonzalez's electronics store in Washington, D.C., over the past…
A: Find the given details below:
Q: Obtain the trend projection with regression forecast for weeks 10 - 13. (Enter your responses…
A: To compare the fits of various forecasting and smoothing approaches, we must employ the MAPE, MAD,…
Q: wine sold by the Connor Owen winery in an eight-year period is as follows: YEAR CASES OF MERLOT…
A: Given :To find :Forecast for year 8 using exp. smoothing
Q: For the given forecast, the tracking signal = MADS (round your response to two decimal places).
A: The tracking system is a concept that helps to analyze the performance of a forecasting method or…
Q: Demand for oil changes at Garcia's Garage has been as follows Month January February March April May…
A: Linear regression forecasting is a statistical technique used to predict or forecast future values…
Q: The most naive forecast can is quite valuable in leading to an organization’s success because it is…
A: The naive forecast can be used as a quick and convenient benchmark to compare the expense and…
Q: Qualitative forecasts and causal forecasts are not particularly useful as inputs to inventory and…
A: Qualitative forecasts and casual forecasts are not specifically helpful as inputs to the inventory…
Q: If the weights for a moving average forecast with a span of 4 are: 0.4,0.2,0.3,0.1…
A: The objective of the question is to identify potential problems with the given weights for a moving…
Q: discuss
A: The answer to this question is false.
Q: The following data are for calculator sales in units at an electronics store over the past nine…
A: Given Sales data-
Q: Forecasting is a prediction rather than a reality
A: The term forecasting is a technique that uses the historical data as inputs to make the informed…
Q: 2. Simple moving average using Excel: Calculate demand forecast for weeks 6-20 using 5 week simple…
A: Forecasting is predicting the demand/sales in advance for future periods. Moving average forecast is…
Q: The number of cases of merlot wine sold by the Connor Owen winery in an eight-year period is as…
A: Forecasting is a technique that is adopted by every business to make informed decisions about the…
Q: Using an exponential smoothing model with an alpha value of 0.30, estimate the smoothed value…
A: Below is the solution:-
Q: The following data are for calculator sales in units at an electronicsstore over the past 9…
A: In order to find Trend projection, Trend equation using regression is as follows: Where, and…
Q: Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be…
A: Using least Square method Marron 5 TV appearancr(X) Demand for Guitars(Y X^2 Y^2 XY 3 4 9 16…
Q: If the weights for a moving average forecast with a span of 4 are: 0.3,0.2,0.2,0.4…
A: The objective of the question is to identify potential problems with the given weights for a moving…
Q: The following table shows predicted product demand using your particular forecasting method along…
A: From the above given information, we have to compute the tracking signal of each period using the…
Q: After using your forecasting model for six months, you decide to test it using a tracking signal.…
A: Period ForecastActualMay450500June500550July550400August600500September650675October700600
Q: A company which installs swimming pools has recently merged with another regional installer. It is…
A: Forecasting in advance helps to estimate the sales that could be generated in the future period.…
Q: Apple's stock price has performed very well over the last decade. In May 2016, Apple stock dropped…
A: For week 54, the stock price of Apple will be $ 150.43 per share.Explanation:In order to solve the…
Q: Assuming a forecast for Week 2 of 48 cases (f2 = 48), generate forecasts for Weeks 13 using…
A: The exponential smoothing forecasting method is a statistical technique for estimating future values…
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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_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 file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?
- 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 owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?
- The file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?Under what conditions might a firm use multiple forecasting methods?
- A small computer chip manufacturer wants to forecast monthly ozperating costs as a function of the number of units produced during a month. The company has collected the 16 months of data in the file P13_34.xlsx. a. Determine an equation that can be used to predict monthly production costs from units produced. Are there any outliers? b. How could the regression line obtained in part a be used to determine whether the company was efficient or inefficient during any particular month?Suppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.
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