Explain the distinction between short- and long-term forecasts?
Q: snip
A: When one forecasting technique is more accurate than another technique when applied to past data the…
Q: Explain the term “wrong” as it pertains to a good forecast?
A: In forecasting techniques, the word "wrong" refers to a difference between the real and forecasted…
Q: Discuss the basic assumptions made when using time series forecasting techniques as opposed to…
A: Several assumptions are made during the Time Series Initial Phase.
Q: Explain what benefits as a forecasting tool does exponential smoothing have over moving averages?
A: In today's environment, when events change frequently, the exponential smoothing method is superior.…
Q: 12. Under the bottom-up approach, a central person or persons take the responsibility for…
A: The method of predicting future outcomes based on past and present data by analyzing the trends is…
Q: Explain why it's important to keep track of forecasting errors.
A: For a time series or other phenomenon of interest, forecast error is the difference between the…
Q: Explain when to use of a time series forecasting techniques and what assumption are made ?
A: The statistical procedures perform statistical analysis on historical data to forecast the…
Q: Contrast the reactive and proactive approaches to forecasting. Give several examples of types…
A: When one talks of proactive and reactive approaches to forecasting, it basically means that one has…
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: Identify the three forecasting time horizons. State anapproximate duration for each.
A: With the help of forecasting we can predict what will be happing in the future. It can be done by…
Q: Who needs to be involved in preparing forecasts?
A: The manager ultimately has the key responsibility to prepare the forecast. An organization should…
Q: Describe the different forecasting methods and provide an example of when each is most applicable.
A: Below is the solution:-
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…
Q: Contrast the use of MAD and MSE in evaluating forecasts?
A: Forecasting is the process of identifying the demand accurately for future production planning and…
Q: What are ways of managing a poor forecast?
A: A bad forecast presupposes that there has been a mismatch between the demand and supply as a result…
Q: State and describe the steps involved in developing a forecasting system
A: To be determined: the steps involved in developing a forecasting system
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: 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: Explain the similarities and differences between quantitative forecasting and qualitative…
A: Forecasting refers to the process of making predictions for the future using past and present data.…
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 what forecasting techniques makes use of written surveys or telephone interviews
A: Operations management manages the internal operation. It starts with the procurement and ends with…
Q: Explain the value of seasonal indices in forecasting. How areseasonal patterns different from…
A: Forecasting can be defined as the way or a process of making predictions based on past events or…
Q: What is forecast accuracy and what are the different methods to check it?
A: Forecast Accuracy is basically how accurately the predicted value matches the actual value. In…
Q: What benefits does exponential smoothing have over moving averages as a forecasting tool?
A: As a forecasting function, exponential smoothing has the following benefits over running averages:…
Q: Explain the term forecasting with least squares
A: Forecasting is a way of making a broader basis about the coming supported by facts. It can be used…
Q: Here are the errors associated with a particular forecast over the past five months, in…
A: Forecasting is a methodology that uses past information as input to make well-informed predictions…
Q: Types of Forecasts that might be needed in IKEA
A: Let’s first understand the meaning of Forecasting and types of Forecasting. Forecasting can be…
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: Describe when to use of a time series forecasting techniques and what assumption are made?
A: Statistical approaches are used to forecast variables by analysing historical data. Forecasts are…
Q: What are the main advantages that quantitative techniques for forecasting have over qualitative…
A: Forecasting is the process of estimating potential demands as well as the resources that will be…
Q: An example of the Quantitative Method of forecasting is
A: Businesses and salespeople can use quantitative forecasting, an objective, data-based process, to…
Q: Explain the Principles for the Forecasting Process?
A: There are many forecasting models and they differ in degree of complexity and amount of the data…
Q: Explain the difference between qualitative and quantitative approaches to forecasting. Describe…
A: Forecasting is the method of forming foresight dependent on historical and existing or present…
Q: Explain how do exponential smoothing have benefits over shifting averages as forecasting tool
A: The merits of autoregressive moving as a prediction approach are considerable in comparison to…
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: Describe List features common to all forecasts?
A: It is the process of estimating future demand using the present and past data. The demand is…
Q: Describe the uses of qualitative, time-series, and causal forecasts.
A: Qualitative Forecasts are used when data as a historical series is not available, or is not relevant…
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: Discuss what advantages as a forecasting tool does exponential smoothing have over moving averages?
A: In today's environment, when events change often, the exponential smoothing method is optimal.…
Explain the distinction between short- and long-term
Step by step
Solved in 2 steps
- 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 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?Explain the trade off between responsiveness and consistency in a time series forecasting system?What does the term "adaptive forecasting" mean?
