Does double exponential smoothing always forecast better than simple exponential smoothing when we suppose that there is a increasing or decreasing trend.
Q: Explain the term for forecast that is used for making day to day decisions about meeting demand
A: The forecasting cycle of an organization is partitioned into two sections including strategic and…
Q: formula refers Naive Forecast method. O a. Forecast value for the current period = Last
A: To compute a naïve forecast just require the earlier month of sales and plug it in close to the…
Q: Simple exponential smoothing with α= 0.3 is being used to forecast sales of digital cameras at…
A: Given Information: Sales in September: 120 units Forecast in September: 100 units Alpha = 0.3…
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: 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: Simple exponential smoothing with a 5 0.3 is being used to forecast sales of digital cameras at…
A: Given Smoothing constant a=0.3 Forecast for September = 100 cameras Sales in September = 120 cameras
Q: No single forecast methodology is appropriate under all conditions True or false?
A: Answer: What is Forecasting: Forecasting is an attempt to predict future events which will be used…
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: Jsing trend-adjusted exponential smoothing, Forecasts (F,), Trend (T,), and Forecasts Including…
A: Given: α=0.20β=0.41(F1)=9 unitsT1=2 units Months Actual Demand (At) Forecast (Ft) Trend (Tt)…
Q: Period Actual 1 12 2 15 16 4 16 Given the information in the following table, Use exponential…
A: Note: - Since the actual data for period 5 is not given, the trend-adjusted forecast can be made by…
Q: When a business is started, or a patent idea needs funding, venture capitalists or investment…
A: A profitability forecast is a set of figures included in a business plan. The result of forecasting…
Q: Obtain the linear trend equation for the following data on new checking accounts at Fair Savings…
A: Linear trend equation is given by: y = a+bx here, a = intercept and b = slope Formulas used: a = ∑y…
Q: How to use the simple exponential smoothing method
A: Exponential smoothing is a period series estimating technique for univariate information that can be…
Q: Using the exponential smoothing forecast, is it possible to forecast a demand that isbigger than any…
A: Exponential Smoothing:- Like the past 2 techniques, guileless and moving midpoints, the dramatic…
Q: Describe the exponential smoothing forecast?
A: In exponential smoothing forecasting, all the values of past demand are taken into consideration by…
Q: Forecast accuracy decreases with the long range forecast. True or False? Explain
A: Forecasting is a technique of predicting future events based on historical data and projecting them…
Q: What is the basic difference between a weighted moving average and exponential smoothing?
A: A Weighted moving average is a quantitative prediction technique tool used to foresee the price or…
Q: exponential functions for trend data. Assume an initial exponential Forecast of 620 units in period…
A: Below is the solution:-
Q: is based on the principle of using only the last observation in a sequence of stable data as a…
A: Option C is correct. The naive forecast is based on the principle of using only the last observation…
Q: Given is a historical time series for job services demand in the prior 6 months. Month Demand 1…
A: The weighted average is a forecasting method in which higher weight is given to the most recent data…
Q: orecast demand for each week, including week 10, using exponential smoothing with a 5 .5 (initial…
A: Exponential smoothing is forecasting method which identifying the farecasting value based on the…
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: The forecast for the month of November was higher than the actual demand and the forecast for the…
A:
Q: exponential smoothing with a smoothing constant equal to .20, assuming a March forecast of 19(00).
A: To find Exponential smoothing with a smoothing constant equal to .20, assuming a March forecast of…
Q: what are the benefits of exponential smoothing forecasting?
A: Forecasting is the process of prediction in which sales demand is estimated using historic…
Q: Predict the forecast for week 35 using an exponential smoothing with a smoothing constant of 0.20.
A: Forecasting is the process of prediction in which sales demand is estimated using historic…
Q: Describe how is the moving average approach equivalent to exponential smoothing?
A: Forecasting, most notably in Time Set, forecasts future values based on historical data. Two…
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: When a product is new and there is no historical data, the most promising method to forecast this…
A: For forecasting a new product with no historical data, Analogy is the most promising method.
Q: Three popular measures of forecast accuracy are: average error, median error, and maximum error.…
A: The accuracy of the forecast can be determined by comparing the actual or real values with the…
Q: Forecast bias is useful to determine a. Seasonality b. Trends c. if forecast error is…
A: A forecast bias happens when there are differences between actual outcomes and previously generated…
Q: Explain how is the moving averages approach equivalent to exponential smoothing?
A: This question is related to the topic Forecasting approaches and this topic falls under the…
Q: Forecast is calculating estimates of future cycle/s based on data of past cycles, there is no…
A: Forecasting is the way toward making expectations dependent on over a significant time span…
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: Given the Exponential Smoothing Method, Actual Demand alpha = .25 and Forecast Demand alpha = 0.75,…
A: The formula for forecast using the exponential smoothening method.
Q: How can we monitor and control forecast in our interior designing business. Please provide with a…
A: Small Introduction about Forecast Control Because forecast explosion only creates exploded forecast…
Q: what is the advantage of using double exponential smoothing over regression?
A: You can use both double exponential smoothing and regression to forecast a demand pattern with a…
Q: Forecasting with exponential smoothing has been compared to driving a car while gazing in the…
A: To be determined: Forecasting with exponential smoothing has been compared to driving a car while…
Q: Sales volume of July was 390 Use exponential smoothing with a smoothing constant to find the…
A: Forecasting is the process of making assumptions of future events based on past and present…
Q: Explain how is the moving average equivalent to exponential smoothing
A: Moving approaches of smoothing and exponential average:
Q: Describe why such forecasting devices as moving average , weighted averages and exponential…
A: To be determined: why such forecasting devices as moving average , weighted averages and…
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 advantages does adjusted exponential smoothing have over a linear trend line for forecasted…
A: Adjusted exponential smoothing is a forecasting methodology that employs measurable and historical…
Q: Given an actual demand this period of 105, a forecast value for this period of 100, and an alpha of…
A: n exponential smoothing forecast, Next forecast = Previous forecast+α(Actual-Previous forecast)
Q: Use trend-adjusted exponential smoothing to forecast the firm’s August income. Assume that the…
A: Trend-adjusted exponential smoothing is a method that uses measurable, historical data observations,…
Q: Using the double exponential smoothing forecast, is it possible to forecast a demand thatis bigger…
A: Forecasting is a prediction method that can use historical data and current market trends and…
Step by step
Solved in 2 steps
- 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_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_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 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_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?
- 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.At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.The management of a technology company is trying to determine the variable that best explains the variation of employee salaries using a sample of 52 full-time employees; see the file P13_08.xlsx. Estimate simple linear regression equations to identify which of the following has the strongest linear relationship with annual salary: the employees gender, age, number of years of relevant work experience prior to employment at the company, number of years of employment at the company, or number of years of post secondary education. Provide support for your conclusion.