1. What is the tracking signal for the forecast?
Q: A quality control manager wants to check the accuracy of the exponential smoothing with trend…
A: Find the given details below: Given details: Period Actual Sales Quarter 1 200 Quarter 2…
Q: Month 1 2 3 4 5 No. of Cases 105 115 120 120 125 Month 6 7 8 9 10 No. of Cases 125 130 140 145 150…
A: Given data is
Q: snip
A: When one forecasting technique is more accurate than another technique when applied to past data the…
Q: The company Handy Inc. produces a solar-powered electronic calculator that has experienced the…
A: 1) From the data given :-a) Moving average with N=3 forecast is given as :- Ft=Dt-1+Dt-2+Dt-33…
Q: Choose the type of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend,…
A: Delphi Technique of forecasting would be appropriate to predict the demand for vacations on the…
Q: Series forecasting for Business| The F-test used in testing the significance of a regression model…
A: The correct answer is
Q: b. Use the least-squares regression method to derive a forecasting equation. c. What is your…
A: Since you have posted a question with multiple sub-parts, we will solve the first three subparts for…
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: Using the data set below, what would be the forecast for period 5 using the exponential smoothing…
A: Forecasting is the process of estimating future sales or demand using previous data and information.…
Q: Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the…
A:
Q: d) Calculate the trend projection with regression forecast for periods 7 through 10. The regression…
A: Forecasting is the ability to predict future happenings using different forecasting methods.
Q: The following equation summarizes the trend portion of quarterly sales of condominiums over a long…
A: Forecasting is a method that produces accurate estimates using historical data as inputs to…
Q: Use exponential smoothing with a=0.2 and a=0.5 to generate forecasts for periods 2 through 6. Use…
A:
Q: You discovered that the forecasting error falls beyond the acceptable ranges in the past three…
A: Find the given details below: Given details: Period Actual Forecast (A-F) Error (A) (F)…
Q: I'm trying to forecast how many TV's my shop will sell in 2021. I have data for the previous 4…
A: Forecasts generated applying exponential smoothing techniques are weighted averages of preceding…
Q: Company XYZ is a movie distribution company. It has kept records of total annual movie ticket sales…
A: Forecasting is a method which helps to predict the future based on the given identified past…
Q: The following gives the number of accidents that occurred on Florida State Highway 101 during the…
A: Find the given details below: Given details Month Number of Accidents Jan 25 Feb 45 Mar…
Q: Consider the data below which includes sales data and the forecasts that would have been made using…
A: Given data is
Q: Consider the monthly sales data of a company for last year as well as first six month data for…
A: Given information:
Q: Accuracy of forecasts. The manager of a large manufacturer of industrial pumps must choose…
A: Given data, Assume that each forecast has an average error of zero. Forecast Month…
Q: Given the following data, use exponential smoothing with a = 0.1 and a = 0.6 to generate forecasts…
A: Given data a=0.1 and 0.6 as smoothing constants MAD AND MSE which is better Exponential smoothing…
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: c. Using simple exponential smoothing, what would your forecast be for this month if the…
A:
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: Number of Accidents 25 45 64 95 Using the least-squares regression method, the trend equation for…
A: NOTE: We are allowed to do only one question at a time. The regression equation is of the form:…
Q: The manager of a large manufacturer of industrial pumps must choose between two alternative…
A: Both techniques have been used to prepare forecasts for a six month period as follows:
Q: Sales of Volkswagens have grown steadily at auto dealerships in Nevada during the past 5 years (see…
A: Given data is
Q: Explain the trade off between responsiveness and consistency in a time series forecasting system?
A: Tradeoff A tradeoff is a decision-making technique that involves sacrificing quality, quantity, or…
Q: . Using POM for Windows' least squares-linear regression module, develop a relationship to forecast…
A:
Q: What three methods are used to determine the accuracy of any given forecasting method? How would you…
A: Forecasting is the process of making assumptions of future events based on past and present…
Q: Consider the following sales data for Bell, Inc. Month Sales ($ Millions) Jan. 10 Feb. 12 March…
A: Weighted moving average M - M=∑i=nWt ×Vt∑i=nWt Where M = Moving Average Value V= Actual value W…
Q: Lenovo uses the ZX-81 chip in some of its laptop computers. The prices for the chip during the past…
A: Note: As per the Bartleby guidelines, only the first two parts have been answered.
Q: d. Follow part (b) above but using an alpha of 0.8 this time. Discuss the forecasting errors…
A: Absolute error is the error between the forecasted value and the actual value of the set.
Q: a. Forecast April through September using a three-month moving average. b. Use simple exponential…
A: Below is the solution:-
Q: sing data in columns A-C create a forecast using the Simple Moving Average method based on 10 weeks…
A: Forecasting means predicting in advance the values of future sales/demand by using different methods…
Q: Here are the data for the past 21 months for actual sales of a particular product: LAST YEAR THIS…
A: Given: Weight for the recent quarter or (3rd quarter) = 0.50 Second most recent or (2nd quarter) =…
Q: a) Use a 2-month moving average on all the data and plot the averages and the prices. b) Use a…
A: The mean absolute deviation(MAD) shows the errors in the forecasted values from the actual values.…
Q: An analyst must decide between two different forecasting techniques for weekly sales of roller…
A: MAD stands for mean absolute deviation. Whereas, MSE stands for mean squared error. These are the…
Q: . What is the mean square error for time periods 2 through 4 using the average forecasting method?…
A: I am using the 2 periods simple moving average method to find average forecasts. It is the average…
Q: Why the following Approaches are used in forecasting, how would you interpret them what do they mean…
A: Forecasting is a technique that a marketer uses to estimate various things like a trend, future…
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: 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: Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be…
A: Using least Square method Marron 5 TV appearancr(X) Demand for Guitars(Y X^2 Y^2 XY 3 4 9 16…
Q: a. Develop a regression equation to forecast the cost per thousand gallons as a function of the…
A: In statistics, a regression equation is used to determine whether or not there is a link between two…
Q: a. Use linear regression to find a relation to forecast Y, which is the quality parameter from the…
A: The Equation of Linear Regression, The equation is Y= a + b*X, where Y is the dependent variable…
Q: b) The forecast for the next month (Jan) using the naive method= 22 sales (round your response to a…
A: Forecasting is the process of predicting future events or trends based on past and present data.…
- Use regression or simple exponential smoothing with the following data. For exponential smoothing, assume the
forecast for year 1 was the same as the actual and use an alpha of 0.7. (use excel to show formauls used)
Year |
Sales |
1 |
290 |
2 |
340 |
3 |
400 |
4 |
410 |
5 |
400 |
1. What is the tracking signal for the forecast?
Step by step
Solved in 2 steps with 5 images
- 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 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?
- Under what conditions might a firm use multiple forecasting methods?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?
- 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_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_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?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?