What is the mean absolute deviation (MAD)? Why is it useful in forecasting?
Q: How do exponential smoothing advantages have over moving averages as a forecasting tool?
A: The advantages of exponential smoothing as a forecasting method over operating averages are as…
Q: Explain the benefits does exponential smoothing have over moving avarages as a forecasting tool ?
A: While in Moving Averages the previous perceptions are weighted similarly, Exponential Smoothing…
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A: Forecast Error = 4, 8, and -3 Forecast Error | Forecast Error| Error2 1 4 4 16 2 8 8 64 3…
Q: Choose the type of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend,…
A: Forecasting techniques are used to predict the future on the basis of past and present data.…
Q: Given forecast errors of 4, 8, and −3, what is the mean absolute deviation (MAD) and mean square…
A: Forecast errors = 4,8 and -3 Absolute errors = 4, 8 and 3
Q: What are the basic assumptions made when using time series forecasting techniques as opposed to…
A: Stationarity: The first assumption is that the series of data points are stationary. The series is…
Q: Select the most suitable forecasting technique (survey, Delphi, averaging seasonal, naive, trend, or…
A: Forecasting may be a technique that uses historical knowledge as inputs to form educated estimates…
Q: Think of an industry or company other than automotive that relies heavily on forecasting accuracy.…
A: Forecasting is completely based on past data, unlike predictions that are based on instinct, or…
Q: Explain the basic assumptions made when using time series forecasting techniques as opposed to…
A: The Time Series Initial Phase makes a variety of assumptions.
Q: When should time series forecasting techniques be used?
A: The statistical data and, as a consequence, the projected features are analyzed using statistical…
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A: Given errors are: 3, 2, -2, 9 Running Sum of Forecast Errors (RSFE), is given by: RSFE = ∑ Errors…
Q: Given four forecast errors of 3, -1, -4 and 3. What is the tracking signal that results from these…
A: The concept of Operation Management: Operation management is the management that applies to a…
Q: Do you think that hard rock cafe makes use of time horizons when forecasting?
A: The forecast horizon is that the duration of your time into the destiny that forecasts are to be…
Q: Discuss when is time series forecasting used?
A: Forecasting is a strategy for forecasting future events using historical data and knowledge.
Q: What forecasting methods should the company consider? Please justify.
A: Forecasting is a prediction method that can use historical data and current market trends and…
Q: There are two general methods to forecasting:Even, what is their meaning?
A: The organization's forecasting is critical. External forces are used to forecast, and a few…
Q: Which qualitative forecasting technique was developed to ensure that the input from every…
A: Delphi method.
Q: Explain what can a company do to resolve the problem of forecasting accuracy?
A: Forecasting is the technique of anticipating the future using facts from the past and present.…
Q: 12-1. The Hartley-Davis motorcycle dealer in the Minneapolis- St. Paul area wants to be able to…
A: Given - Month Sales January 9 February 7 March 10 April 8 May 7 June 12 July 10…
Q: What can a business do to address the issue of forecasting inaccuracy ?
A: Predicting final demand is a critical role of the supply chain. Numerous businesses are unaware of…
Q: What implications do forecast errors have for the search for ultrasophisticated statistical…
A: Forecasting is the process of making predictions for the future based on the past and present data.…
Q: How has the technology had an impact on forecasting?
A: Technology plays an important role in forecasting and has the ability to have a huge impact. We will…
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A: The quantitative forecasting techniques require the past relevant data, the absence of this makes…
Q: Explain the trade off between responsiveness and consistency in a time series forecasting system?
A: Tradeoff A tradeoff is a decision-making technique that involves sacrificing quality, quantity, or…
Q: What is the purpose of establishing control limits for forecast errors?
A: Forecast errors are described as the difference between the forecast of a particular period and that…
Q: Justify the trade-off between responsiveness and consistency in a time-series forecasting system.
A: TradeoffTradeoff is a situational decision taken approach, that involves diminishing quality,…
Q: exponential smoothing superior to moving averages
A: Remarkable smoothing is a general guideline method for smoothing time arrangement information…
Q: Sales of hair dryers at the Walgreens stores in Youngstown, Ohio, over the past 4 months have been…
A: Note- We’ll answer the first three subparts of the question since the exact one wasn’t specified.…
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A: A moving average forecast becomes less responsive to change in a data series when more data points…
Q: What is 'forecasting error'? What are the metrics used in measuring forecasting errors?
A: Forecasting Error A prediction error is the difference between the actual or real value of a time…
Q: List the analytical tools and methods used in forecasting?
A: Forecasting is the process of making assumptions of the future on the basis of past and present data…
Q: Give an example of forecasting a pet store
A: The forecast is defined as the projection based on past data. Past data, though, is factual, yet…
Q: Identify and explain the areas other than mentioned where the Hard Rock Cafe could use forecasting…
A: Hard Rock Cafe, Inc. is a chain of subject eateries established in 1971 by Isaac Tigrett and Peter…
Q: Discuss the basic assumptions made when using time series forecasting techniques as apposed to…
A: Time series forecasting fundamental assumptions:
Q: Explain when is time series forecasting used ?
A: Forecasting is the process of predicting future events based on previous data and information.
Q: Over the past 6 weeks, some overseas wholesalers lowered their exports past 6 weeks shipments…
A: First of all, we have to list down the values in excel sheet
Q: State and explain the weakness of standard forecasting technique in forecasting approaches
A: To be determined: the weakness of standard forecasting technique
Q: what is the main difference between casual methods and time series methods used in forecasting?…
A: This question is related to the topic of the forecasting approach and this topic falls under the…
Q: Explain the advantages of forecasting tool does exponential smoothing over moving avarages ?
A: The key benefits of exponential smoothing versus moving averages as a forecast.
Q: State examples of industries affected by seasonality and reasons to eliminate seasonality in their…
A: To be determined: examples of industries affected by seasonality and reasons to eliminate…
Q: What does the term "adaptive forecasting" mean?
A: Forecasting is nothing more than forecasting patterns and making potential forecasts based on…
What is the mean absolute deviation (MAD)? Why is it useful in
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- 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_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 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_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_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_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_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?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.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?