a. Find the tracking signal for each month. (Negative values should be indicated by a minus sign. Round your answers to the nearest whole number.) b. Does the model used here give acceptable answers? multiple choice No, the model's performance is poor. Yes, the model's performance is good.

a. Find the tracking signal for each month. (Negative values should be indicated by a minus sign. Round your answers to the nearest whole number.) b. Does the model used here give acceptable answers? multiple choice No, the model's performance is poor. Yes, the model's performance is good.

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.7: Exponential Smoothing Models

Problem 25P: The file P13_25.xlsx contains the quarterly numbers of applications for home mortgage loans at a...

See similar textbooks

Related questions

Q: a. Obtain the linear trend equation for the following data on new checking accounts at Fair…

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: The director of the Riley County, Kansas, library system would like to forecast evening patron…

A: A seasonal index is a model of how a distinct season for some period correlates with the average…

Q: Week Passengers 440 11 446 12 451 13 455 14 464 15 996 474 17 476 18 482 a. Explain why an averaging…

A: After observing the data, we can see that there is an upward increasing trend. In case the average…

Q: Demand for oil changes at Garcia’s Garage has been as follows:Month Number of Oil…

A: The following dialogue box will appear. Enter the data and click on OK.

Q: which of the following is a technique used to determine forecasting accuracy A. Mean Absolute…

A: There is a difference between forecasting and finding the accuracy of the forecast and one might…

Q: Consider the following time series data. Month 1 2 3 4 5 6…

A: MSE stands for Mean squared error. It calculates the average squared difference between the forecast…

Q: Month 1 2 3 7 8 9 10 11 12 Flat-Screen Sales 30 32 30 39 33 34 34 38 36 39 30 36 a) Determine the…

A: Find the given details below: Given Details: Month Flat Screen Sales 1 30 2 32 3 30 4…

Q: Consider the following time series data. Week 1 2 3 4 5 6 Value 18 13 16 11 18 15 Using the…

A: The naïve method of forecasting uses the value of the previous week as the current week's forecast.…

Q: 1. Solve manually. The following gives the number of pints of type A blood used at Woodlawn Hospital…

A: Given-

Q: The Grand Bakery produces 60 special sourdough rolls every day. Any rolls that are not sold each day…

A: Forecasting is the process of prediction in which sales demand is estimated using historic…

Q: All forecasting methods using exponential smoothing, adaptive smoothing, and exponential smoothing…

A: Forecasting is the process of predicting future demand values based on historical data. The…

Q: A check-processing center uses exponential smoothing to forecast the number of incoming checks each…

A: Given Forecast S(June) = 42 million Checks in June X(June) = 40 million Smoothing constant α=0.2

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: An analyst must decide between two different forecasting techniques for weekly sales of roller…

A: Given data-

Q: Determine the Running Sum of Forecast Errors (RSFE), the Mean Absolute Deviation, MADt-1,and the…

A: Forecasting is the process of predicting future demand based on previous or historic information and…

Q: The number of fishing rods selling each day is given below. Perform analyses of the time series to…

A: Note: - Since we can answer up to three subparts, we will answer the first three subparts here. If…

Q: 2. National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven- month…

A: Here, from the question, I have got the tabulated data, for this data, I have applied various…

Q: omplete the data on the table by considering the forecasting method indicated in each column. Show…

A: Forecasting means predicting in advance what would be the estimated sales of future periods by…

Q: Bradley’s Copiers sells and repairs photocopy machines.The manager needs weekly forecasts of service…

A: Given data, Week Actual Services level 1 29 2 27 3 41 4 18 5 33 Exponential…

Q: Exercise # 2 –Calculating MADt, Revised MADt,Error,and the Revised Error :Has the Forecast Improved…

A: 2 period moving average forecast for revising: -

Q: Forecasts based on averages. Given the following data:PeriodNumber ofComplaints1 602 653 554 585…

A: Formula: Answer:

Q: Given that the previous forecast of 65 turnedout to be four units less than the actual demand; the…

A: In simple exponential smoothing method, forecast for period t can be calculated using the following…

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: A production company was able to hit the following sales order for the past 3 months: 45% of 420pcs…

A: Given data is

Q: Calculate the 2-month Moving Average Forecast for sales from March/2019 to a) January/2019 and enter…

A: Below is the solution:-

Q: An analyst must decide between two different forecasting techniques for weekly sales of roller…

A: Linear trend equation: Ft = 124 + 2.1t. When t = 11, forecast for the 11th period will be 124 + 2.1…

Q: What is the definition of a forecast error?a. The average difference between the forecast and the…

A: Forecasting is a tool that uses historical data as inputs that are predictive in deciding the path…

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: The forecasting technique that gives progressively lower weights to all past data without dropping…

A: Forecasting is a method that utilizes recorded information as inputs to construct declared…

Q: Corporate triple-A bond interest rates for 12 consecutive months follow. Month 1 2 3 4 5 6 7 8 9 10…

A: a)

Q: c. Using simple exponential smoothing, what would your forecast be for this month if the…

Q: 25. Determine the following: a. The value of a consistent with N = 6 in moving averages. b. The…

Q: a) Forecast the number of disk drives to be made next year, using linear regression. b) Compute the…

A: Use the fax machine data to model the relationship between cumulative fax machines produced and…

Q: a. What is your forecast for December of Year 4, making period 1 as the starting period for the…

A: a) Period Demand Square of X Multiplication of x and y, XY 1 4507 1 4507 2 4400 4 8800…

Q: 13. Two forecasting methods have been used to evaluate the same economic time series. The results…

A: Formula:

Q: The manager of a popular tourist resort wants to use the manual trend projection forecasting…

A: The equation for exponential smoothing is- Ft = F t-1 + α(A t-1 – Ft-1) Ft = the exponentially…

Q: Consider the following time series data. Choose the correct time series plot. (i) (ii)…

A: A time series is a grouping of information focuses that happen in progressive requests throughout…

Q: Handy, Inc., produces a solar-powered electronic calculator that has experienced the following…

A: All the sales value in thousands So to calculate the forecasted May month sales the formula we put…

Q: 2. Simple moving average using Excel: Calculate demand forecast for weeks 6-20 using 5 week simple…

A: Forecasting is predicting the demand/sales in advance for future periods. Moving average forecast is…

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: A restaurant wants to forecast its weekly sales. Historical data (in dollars) for 15 weeks are…

A: Forecasting refers to the statistical technique used for predicting the future demand and sales of…

Q: 2. Suppose that the University of the West had the following data of its growth of enrollment from…

A: Since you have posted a question with multiple sub-parts, we will solve first three sub-parts for…

Q: a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a…

A: ANSWER IS AS FOLLOWS:

Q: 0. During the past five months the emergency new County Hospital has observed the number of patients…

A: Seasonal adjustment is a strategy for information smoothing that is utilized to foresee monetary…

Q: Sales of the Crown Gems have been increasing over the past five years. The operations manager has…

A: Forecasting entails making educated guesses at unknown values based on known values. Exponential…

Q: The actual demand for the patients at EYE OPD of KTH for the first six weeks of this year follows…

A: Given data is

Q: A time series with forecast values and error terms is presented in the following table. The mean…

A: Following table shows the calcuations: Month Actual, Yt Forecast, Ft Error |Yt-Ft|/Yt July 5…

Concept explainers

Forecasting in Business

Forecasting is the process of predicting the future based on the past and the present data and circumstances. In other words, forecasting is the act of making a detailed analysis of future events based on the decisions made in the past as well as the present. Forecasting plays a very important role in operational management as it helps in planning and decision-making. It is not only important for the success of a business but also contributes to individual growth and success. Many business organizations or companies have failed due to the shortcomings of their forecasting.

Question

A particular forecasting model was used to forecast a six-month period. Here are the forecasts and actual demands that resulted:

	FORECAST	ACTUAL
April	256	206
May	328	252
June	403	330
July	353	305
August	378	324
September	452	395

a. Find the tracking signal for each month. (Negative values should be indicated by a minus sign. Round your answers to the nearest whole number.)

b. Does the model used here give acceptable answers?

multiple choice

No, the model's performance is poor.
Yes, the model's performance is good.

Leveraging special tenchniques in analyzing historical data to predict future trends. Forecasting covers the methods and types of forecasting and their application to case studies.

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Step 1

VIEW

Step 2

VIEW

Step 3

VIEW

Trending now

This is a popular solution!

Step by step

Solved in 3 steps with 1 images

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, operations-management and related others by exploring similar questions and additional content below.

Similar questions

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_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_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 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_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_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?
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?
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?
The file P13_19.xlsx contains the weekly sales of a particular brand of paper towels at a supermarket for a one-year period. a. Using a span of 3, forecast the sales of this product for the next 10 weeks with the moving averages method. How well does this method with span 3 forecast the known observations in this series? b. Repeat part a with a span of 10. c. Which of these two spans appears to be more appropriate? Justify your choice.
The file P13_27.xlsx contains yearly data on the proportion of Americans under the age of 18 living below the poverty level. 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. Create a chart of the series with the forecasts superimposed from this optimal smoothing constant. Does it make much of an improvement over the model in part b? d. Write a short report to summarize your results. Considering the chart in part c, would you say the forecasts are good?
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.