Explain the trade off between responsiveness and consistency in a time series forecasting system?
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: When to use of a time series forecasting technique, what assumptions are made?
A: The statistic techniques uses statistic on historical data and therefore the variables forecasted.…
Q: Which are the QUALITATIVE TECHNIQUES IN FORECASTING?
A: Forecasting is the process of identifying the demand accurately for future production planning and…
Q: What are the similarities and differences between ridge regression and forecasting?
A: A Small Introduction about Regression Regression analysis is used to predict a continuous dependent…
Q: Identify the critical conditions and trade-offs to take into account when selecting forecasting…
A: When choosing the forecasting technology, the important considerations cost and accuracy are…
Q: In your own words, explain adaptive forecasting.
A: Forecasting is the term which is defined as the technique that uses the data which is historical in…
Q: List the seven steps in the forecasting system?
A: Identify the problem: It is the step where the given problem is analyzed along with all the members…
Q: What advantages does exponential smoothing have over movingcaverages as a forecasting tool?
A: The following are the benefits of exponential smoothing as a forecasting tool over moving averages.…
Q: What is the connection between forecasting and quality control?
A: TQM can be thought of as a control framework for a client organisation that actively promotes…
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 what assumptions do qualitative forecasting systems make
A: Qualitative prediction systems make the following assumptions:
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: Explain when to use a time series forecasting techniques
A: The statistical techniques are applied to past records and hence to the projected variables.…
Q: If the Tracking Signal for your forecast was consistently positive, what could you then say this…
A: If the tracking signal of the forecast is always positive, then it is bias and consistently too low.…
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: Describe in detail what is a time series forecasting model ?
A: Forecasting is a type of prediction approach that can be used to make future judgments based on past…
Q: Explain the relationship between forecasting and quality management?
A: Total quality management (TQM) is a continual process of identifying and avoiding or eliminating…
Q: How do we measure accuracy of a forecasting model?
A: Step1:Forecasting models are tried and tested frameworks of historical data which helps in…
Q: What is a time-series forecasting model?
A: Forecasting is an important instrument to predict the future. Every organization needsforecasting to…
Q: List three qualitative forecasting methods and discuss one of them in details.
A: Qualitative forecasting techniques depend on immeasurable data like views & intuition. The…
Q: Explain four qualitative forecasting techniques ?
A: Planning refers to the process of assessing demand for the goal of future supply chain and…
Q: Explain the methods that are used to develop the forecasting methodology
A: Forecasting is a continuous activity that the business employs in both the short term and long term.…
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: What forecasting technique makes use of written surveys or telephone interviews?
A: Ans- Forecasting is the process of making assumptions of the future on the basis of past and present…
Q: Explain what are some of the potential advantage of a more formalized approach to forecasting
A: Forecasting is a method of accurately anticipating future demand to plan for it. Manufacturing and…
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: snip
A: The quantitative forecasting techniques require the past relevant data, the absence of this makes…
Q: Describe the ASSOCIATIVE FORECASTING TECHNIQUES?
A: Associative forecasting is the technique of forecasting which uses several independent variables as…
Q: Can you tell the difference between "correct" and "true" when it comes to forecasting?
A: Forecasting is important in supply chain management because the production and inventory process of…
Q: Describe the word least-square forecasting?
A: Forecasting is a technique for making educated forecasts based on historical evidence. It is used to…
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: What is seasonality?How do we forecast using data that has seasonality?
A: Seasonality in time series data is the occurrence of repetitive up and down cycles in series values…
Q: Explain the analytical tools and methods used in forecasting ?
A: Many statistical techniques are used to examine the data, which helps to summarize data first from…
Q: Forecasting can be classified into which basic types?
A: Forecasting is the process of identifying the demand accurately for future production planning and…
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: State and explain the value of seasonala indices in forecasting and how are seasonal patterns…
A: To be determined: State and explain the value of seasonal indices in forecasting and how are…
Q: How many steps are there in collaborative planning, forecasting, and replenishment (CPFR)?
A: There are 9 steps in collaborative planning, forecasting, and replenishment (CPFR). They are:
Q: Describe the methods that are used to develop the forecasting methodology?
A: Forecasting is a continuous process that the organisation engages in on both a short and long term…
Q: Give a proper explanation of what is meant by the adaptive forecasting
A: To be determined: a proper explanation of what is meant by the adaptive forecasting
Q: Describe the key factors and trade-offs to consider when choosing a forecasting technique.
A: The main factors are cost and accuracy..
Q: State and describe the forecasting technique which places more emphasis on recent values and explain…
A: To be determined: the forecasting technique which places more emphasis on recent values and explains…
Q: What does the term "adaptive forecasting" mean?
A: Forecasting is nothing more than forecasting patterns and making potential forecasts based on…
Explain the trade off between responsiveness and consistency in a time series
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- What forecasting techniques are used in the management of technology and innovation?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 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 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_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?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?What does the term "adaptive forecasting" mean?
- Explain the trade off of responsiveness in a time series forecasting system ?Explain the relationship between forecasting and quality management?Explain what are the main benefits that quantitative techniques for forecasting have over qualitative techniques? Describe what limitations do quantitative techniques have?