Describe why such forecasting devices as moving average , weighted averages and exponential smoothing are not well suited for data series that have trends
Q: Discuss Qualitative forecasting technique. Explain the situations where we use Qualitative methods.…
A: Forecasting is the process of making assumptions of the future on the basis of past and present data…
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A: When one forecasting technique is more accurate than another technique when applied to past data the…
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A: The Delphi method is more qualitative. The Delphi method was developed by the Rank corporation in…
Q: Consider then, the nature and characteristics of forecasting. What do you think the difficulties or…
A: Forecasting is a method where historical data is used an input to make output in the form of data…
Q: hat are the benefits of exponential smoothing as a forecasting method over running averages
A: The advantages of the exponential smoothing over moving averages with respect to the forecasting…
Q: Explain how do we measure accuracy of a forecasting model
A: We utilize the following criteria to determine a prediction model's efficiency:
Q: Refer to Problem 4.2. Develop a forecast for years 2 through 12 using exponential smoothing with a =…
A: Given data is Alpha = 0.4 Forecast for year 1 = 6
Q: Monthly sales for a six month period are as follows: Month Sales Jan 18,000 Feb 22,000 Mar 16,000…
A: 1). Four-month moving average:
Q: In exponential smoothing, if ɑ = 0.3, then the damping factor for use in forecasting should be: *…
A: Exponential smoothing is a forecasting method which identify the forecasting value using the…
Q: (4-b). Use simple exponential smoothing with α = 0.6 to forecast the tire sales for September…
A: Forecasting sales refers to the prediction of future sales using previous data to estimate the…
Q: Which of the following smoothing constant would make an exponential smoothing forecast equivalent to…
A: alpha of 1.0 leads to an exponential smoothing forecast similar to a naive forecast.
Q: Which of the following smoothing constants would make an exponential smoothing forecast equivalent…
A: In exponential smoothing, it is attractive to utilize a higher smoothing consistent when…
Q: Describe and evaluate the method of forecasting based on a time series analysis when a trend is…
A: Forecasting is the practice of estimating the size of unknown future events and generating different…
Q: 9-The approach that uses the organization's current level of employment as the starting point for…
A: Every business enterprise is required to assess its staffing requirements over a specific time…
Q: State and explain three methods that are used to determine the accuracy of any given forecasting…
A: To be determined: three methods that are used to determine the accuracy of any given forecasting…
Q: Explain what assumptions do qualitative forecasting systems make
A: Qualitative prediction systems make the following assumptions:
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A: An exponential smoothing forecast becomes more responsive to changes in a data series when its alpha…
Q: Compute a 3-month weighted average forecast for months 4 through 9. Assign weights of 0.55, 0.33 and…
A: Forecasting is a technique used to predict future outcomes on the basis of past data. There are…
Q: Clinic administrator Dana Schniederjans wants you to forecast patient numbers at the clinic for week…
A: Forecasting is a process that uses recorded data as inputs to make informed estimates that are…
Q: You are required to collect data about corona virus cases since 1st of AUG 2020 till the day of…
A: The unprecedented Covid-19 has impacted the lives of people worldwide.
Q: Consider the time series data in Table 4 Construct a time series plot. What type of pattern exists…
A: Moving average and exponential smoothing methods are time series forecasting method. This can be…
Q: Is there anything that can be done to boost the Forecast technique
A: Forecasting is a technique for forecasting potential demand, assessing risk, and analysing patterns.…
Q: Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17…
A: Hi, We are supposed to answer 3 sub-parts at a time. Since you have not mentioned which subpart to…
Q: Which of the following concepts explain why we tend to make errors in affective forecasting?
A: Affective forecasting refers to the prediction of future events on the basis of a current emotion.
Q: exponential functions for trend data. Assume an initial exponential Forecast of 620 units in period…
A: Below is the solution:-
Q: The accompanying dataset provides data on the monthly usage of natural gas (in millions of cubic…
A: Given data is Alpha = 0.6 Gamma = 0.8
Q: Sunrise is planning its purchases of ingredients for bread production. If bread demand had been…
A: Exponential smoothing could be a statistic statement technique for univariate information that may…
Q: Which forecasting model assumes that what will happen in the immediately succeeding period is most…
A: Forecasting is a Multi-Criteria Decision Making (MCDM) technique that considers historical data for…
Q: Using MAD as a criterion, which technique has the better performance record?
A: MAD or Mean Absolute Deviation indicating the average value of the absolute errors. An efficient…
Q: All forecasting methods using exponential smoothing, adaptive smoothing, and exponential smoothing…
A: Forecasting is the process of making assumptions of the future on the basis of past and present…
Q: Which qualitative forecasting technique was developed to ensure that the input fromevery participant…
A: Forecasting is the way toward making forecasts of things to depend on at various times information…
Q: a. They generally work best when combined with a quantitative approach
A: Qualitative research comes from open-ended questions. It collects data in a different way. Instead…
Q: You have a data set that includes time period and past sales data, and you want to use a time series…
A: Ans// D) Weighted moving average Time series forecasting makes the prediction about the future by…
Q: All the following are techniques used in quantitative forecasting except. A. Regression analysis B.…
A: Forecasting refers to the approach of making predictions on the basis of present and past…
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: 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: Which time-series forecasting method works best if the company assumes that product demand will…
A: Forecasts are a basic input in the decision processes of operations management because they provide…
Q: While other forecasting methods and techniques are also used, these three are the most notable at…
A: For Walmart's business, effective human resource management is essential. The company's human…
Q: The following set of data represents the quarterly changes in demand for an item over the next 3…
A: When determining the direction of future trends, forecasting is a technique that makes educated…
Q: ontrast the reactive and proactive approaches to forecasting. Give several examples of types of…
A: Forecasting: Forecasting is a technique and a method which takes into consideration a set of…
Q: Qualitative or judgmental forecasting models may use quantitative data. True False
A: False
Q: Averaging forecasting techniques are useful for: a. forecasting seasonal indexes b.…
A: Forecasting is the process of making predictions based on past and present data and most by analysis…
Q: State and explain the weakness of standard forecasting technique in forecasting approaches
A: To be determined: the weakness of standard forecasting technique
Q: 1. It has been said that forecasting using exponential smoothing is like driving a car by looking in…
A: As specified, I have solved the second question for you. Kindly find it's answer ahead and post the…
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: Which one of the following models would be best for new product forecasting? Multiple Choice…
A: Holt's two-parameter model, also called as linear exponential smoothing, is a popular smoothing…
Q: State what is a qualitative forecasting model and it uses under forecasting
A: To be determined: what is a qualitative forecasting model and it uses under forecasting
Q: What does the term "adaptive forecasting" mean?
A: Forecasting is nothing more than forecasting patterns and making potential forecasts based on…
Q: It has been said that forecasting using exponential smoothing is like driving a car by looking in…
A: Exponential smoothing is a time series forecasting technique for univariate data that can be…
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- Under what conditions might a firm use multiple forecasting methods?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_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_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_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_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_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?
- 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_25.xlsx contains the quarterly numbers of applications for home mortgage loans at a branch office of Northern Central Bank. 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? Is it guaranteed to produce better forecasts for the future?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?