Determine the Forecast Error for the data below using the Mean Squared Error (MSE) formula. Month Demand Forecast 16 205 210 17 197 175 18 230 210 19 240 228 20 252 220
Q: Below is a table containing data on product demand for the most recent three months along with the…
A: MAPE - is a statistical measure of how accurate a forecast system is. It measures this accuracy as a…
Q: Ed Rogers owns an appliance store. Sales data on a particular model of a DVD player for the past six…
A: Absolute Error = | Actual sales - Forecast | MAD = Average of Absolute Error
Q: Using a 3 period moving average, what is the forecast for day 8?
A: 3 period moving average is a forecasting model which helps to identify the forecast as the average…
Q: three-period moving average. A weighted average using weights of .50 (most recent), .20 and .30.…
A: forecasting is a method which helps to predict the unknown future based on the known past…
Q: Given an actual demand of 103, a previous forecast value of 99, and an alpha of .4, the exponential…
A: Forecast using the exponential smoothing method: Demand for current period = 103 Forecast for…
Q: Rosa’s Italian restaurant wants to develop forecasts of daily demand for the next week. Th e…
A: Solution - Given that Day Week 1 Week 2 No of Customers No of Customers Tuesday 52 48…
Q: 5-15 Develop a 4-month moving average forecast for Wallace Garden Supply, and compute the MAD. A…
A:
Q: The following table contains the demand from the last 10 months:…
A:
Q: Ed Rogers owns an appliance store. Sales data on a particular model of a DVD player for the past six…
A: Using the above formulae : Actual of May = 51 Forecast of May = 36.25 alpha = 0.4 Forecast of…
Q: Which of the following measures of forecast fit may correctly be used to compare different forecast…
A: Answer as follows:
Q: Complete the "Forecast for tomorrow" column in the table above. Use an exponential smoothing…
A:
Q: Consider the following time series data. Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 a. Use α = 0.2 to…
A:
Q: Use exponential smoothing with trend adjustment to forecast demand for period 11. Let α = 0.5, β=…
A: α = 0.5 β= 0.3 Initial trend value(I) = 12 Initial forecast (Ft) = 200
Q: Below is a table containing data on product demand for the most recent three months along with the…
A: Calculate the MSE
Q: Period 1 2 3 4 5 6 3. Using the table below, forecast using exponential smoothing. Assume the Alpha…
A:
Q: B: Find forecasting error from the following table by using Tracking Signal. Period Actual…
A: The difference in predicted and actual demand values is known as the forecasting error and it is…
Q: Week Cheeseburger Sales 1 354 2 344 3 368 4 317 5 361 Based on historical observations…
A:
Q: Determine the Forecast Error for the data below using the Mean Absolute Deviation (MAD) formula.…
A: Mean absolute deviation or MAD is the mean or average value of the forecast deviation of error for a…
Q: ind Naïve Forecast, Moving Average and Weighted Average based on the data given at the below table.…
A: In the question, we have monthly data for the year 2018, I would apply forecasting techniques to get…
Q: If the forecasted value of the time series variable for one period is 28.5 and the actual value…
A: Forecasted value = 28.5 Actual value = 32
Q: Determine the Forecast Error for the data below using the Mean Squared Error (MSE) formula. Month…
A: Error = Forecast - Actual Demand Absolute Error = Forecast - Actual Demand Squared Error = Absoute…
Q: Determine the Forecast Error for the data below using the Mean Absolute Percentage Error (MAPE)…
A: Error = Demand - Forecast Absolute Error = Positive value of Error Percent Error = (Absolute error…
Q: Compute the weighted average forecast using the following weights: 0.20, 0.30, 0.10, and 0.40
A:
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: Using seasonal relatives. Apple’s Citrus Fruit Farm ships boxed fruit anywhere in the world.…
A:
Q: Determine the Forecast Error for the data below using the Mean Absolute Deviation (MAD) formula.…
A: Given data is
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: (a) Compute the forecast sale using a = 0.20 and a = 0.35 respectively, (b) solve for MAD, SSE, MSE,…
A: Forecasting is the process of estimating the future demand using previous or historic data or…
Q: Passenger miles flown on Northeast Airlines, a commuter firm serving the Boston hub, are shown for…
A: Given-
Q: 1. Compute the exponentially smoothed forecast of calls for each week. Assume an initial forecast of…
A: THE ANSWER IS AS BELOW:
Q: Assume that the actual sales volume were 1,800; 2,000; 1,700; 1,600; 1,900; and 2,100 for Days 1 to…
A:
Q: 160 # 10 You have been given more data on the correlation between average snow fall and plow days.…
A: The question is related to Forcasting. As per least square method. The equation will be: The…
Q: Forecasting Historical records show the past ten Hood Lacrosse games having the following…
A: Forecasting is the process of prediction in which sales demand is estimated using historic…
Q: Suppose you are working for a baking company in Bangladesh. What are the relevant factors you will…
A: Forecasting is the activity of making estimations of future activities based on past and present…
Q: Using naïve method to make a forecast involving data with trend, the forecasted sales volume for…
A:
Q: Consider the following yearly demand values for a particular product. Year Demand 1 360 2 389 410 4…
A: The technical analysis methods used to smooth the data price by creating a regular updated average…
Q: a) Calculate the three-period moving-average forecast for periods 7 through 10. Three-period Period…
A: Given data is
Q: A time-series trend equation is 25.3 + 21x. What is your forecast for period 7? A. 32.3 B.…
A: Forecasting is the process in which future demand is determined by estimation using previous data or…
Q: With the aid of practical examples demonstrate how qualitative, time-series, and causal forecasts…
A: A Small Introduction to Forecast Demand Request anticipating is the most common way of utilizing…
Q: The following table is given. What is the demand forecast for period 13 if the Winter model is used?…
A: Given data: Demand forecast for 8th period = 7056 Trend forecast for 8th period = 227 Observing the…
Q: Use trend adjusted exponential smoothing to obtain forecasts for periods 6 through 10. Use α= 0.50…
A: SOLUTION: 1 alpha = 0.5 beta=0.4 2 MONTH (t) ACTUAL (at) Exponential smoothing Ft =…
Q: Given the actual demand of 300, the previous forecast of 300, and an alpha of 0.048 , which one of…
A: The actual demand =300 The previous forecast = 300 Alpha = 0.048
Q: A)- Explain the calculation method for the Naive Forecast model. B) If at the end of every month…
A: Forecasting the values in advance helps to reduce the cost, and increase profits by reducing wastage…
Q: You have the data on the application during the 8 consecutive year period below Wanted / Find the…
A: Given that: Year Demand 2000 24 2001 48 2002 50 2003 68 2004 60 2005 66 2006 70…
Q: The following monthly sales (in thousands of AUS dollars) of chocolate boxes have been recorded for…
A: Forecasting is a method of foretelling the future based on the outcomes of earlier data. It includes…
Q: Emergency calls to Winter Park, Florida’s 911 system, for the past 24 weeks are as follows: Compute…
A: Below is the solution:-
Q: An exponential smoothing is being used to forecast demand. Which of the following alpha value (or…
A: Answer: The exponential smoothing method is a weighted moving average method which calculates the…
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…
Determine the
| Month | Demand | Forecast |
| 16 | 205 | 210 |
| 17 | 197 | 175 |
| 18 | 230 | 210 |
| 19 | 240 | 228 |
| 20 | 252 | 220 |
Trending now
This is a popular solution!
Step by step
Solved in 2 steps with 1 images
- Under what conditions might a firm use multiple forecasting methods?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_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_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_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_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?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.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?
