Use exponential smoothing with a=0.2 and a=0.5 to generate forecasts for periods 2 through 6. Use MAD and MSE to decide which of the two models produced a better forecast. Period Actual Forecast 1 15 17 2 18 3 14 4 16 5 13 6 16

Use exponential smoothing with a=0.2 and a=0.5 to generate forecasts for periods 2 through 6. Use MAD and MSE to decide which of the two models produced a better forecast. Period Actual Forecast 1 15 17 2 18 3 14 4 16 5 13 6 16

Contemporary Marketing

18th Edition

ISBN:9780357033777

Author:Louis E. Boone, David L. Kurtz

Publisher:Louis E. Boone, David L. Kurtz

Chapter14: Pricing Strategies

Section14.2: Forecasting Demand

Problem 1LO

See similar textbooks

Related questions

Q: Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17…

A: The concept used here is forecasting with Moving averages and forecast evaluation using MAE, MSE and…

Q: Week Actual Forecast Demand 1 52 48 2 42 46 3 56 52 4 45 47 true or false Assume that the actual…

A: The table shows the calculation of forecast of demand using the simple moving average method with 3…

Q: Discuss the basic assumptions made when using time series forecasting techniques as opposed to…

A: Several assumptions are made during the Time Series Initial Phase.

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: The table below shows the demand for a particular brand of microwave oven in a department store.…

A: Given-

Q: Sales for the past 6 months at Computer Success are given here. Month Sales $ January 150 February…

A: Given data is

Q: Use the data below to solve for the following: 2. Naïve method 3. Unweighted 3 month moving average…

A: Note: - As it is specified to answer 2, 3, and 4, we will answer only those. Given data is

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: 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: 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: Given the following historical data, what is the moving-average forecast for period 6 based on the…

A: Calculation of moving average forecast for period 6 based on the last three periods:The formula for…

Q: Explain when to use a time series forecasting techniques

A: The statistical techniques are applied to past records and hence to the projected variables.…

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: If the Tracking Signal for your forecast was consistently positive, what could you then say this…

A: If the tracking signal of the forecast is always positive, then it is bias and consistently too low.…

Q: Develop a 3-weck weighted average forecast for Week 4 through 9 with weights WI - W2 = W3 = 0.2 0.3…

A: A moving average based on weighted average puts weight on the data gathered recently, by multiplying…

Q: a) Forecast the demand for the week of October 12 using a 3-week moving average. b) Use a 3-week…

A: Forecasting is the process of estimating the future demand according to previous or historic…

Q: If the forecasted demand for the week of August 31 is 360 and α = 0.20, using exponential…

A: Calculation of the forecast of each of the week by exponential smoothing method using the formula…

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: Income at the architectural firm Spraggins and Yunes for the period February to July was as follows:…

A: The formula to be used in Trend smoothing, Tt is Tt+1= Tt + beta*(Ft+1 – FITt)

Q: What method would you choose of forecasting technique, which requires subjective inputs obtained…

A: Forecasting is technique which uses past data in order to predict future trends. It is mainly used…

Q: Two different forecasting models were used to forecastsales of a popular soda on a college campus.…

A: Solution - Introduction - [1] Forecasting Model - Forecasting models are one of the numerous methods…

Q: Below you are given the first five values of a quarterly time series of sales. Year Time Series…

A: Find the Given details below: Given details: Year Quarter Time Series Value Y1 1 1 36 2 24…

Q: 4. What is the forecast for the 13th period based on the four-period moving average? Round your…

A: Given data is

Q: B). Using exponential smoothing, calculate the forecasts for months 2, 3, 4, 5, and 6. The smoothing…

A: Find the Calculations below: Formulas:

Q: National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a…

A: Note: - Since we only answer up to 3 sub-parts, we’ll answer the first3. Please resubmit the…

Q: а. Write down the definition of Associative model forecast with appropriate example. b. Compute MAD,…

A: Forecasting involves victimization of past knowledge to come up with a variety, set of numbers, or…

Q: a. Compare a three-month moving average forecast with an exponential smoothing forecast. Use a = .1.…

A: Forecasting is the process of predicting the future demand based on the previous data or demand.

Q: What is the approximate forecast for May using a two-month moving average? Nov. Dec. Jan. Feb. Mar.…

A: Since you have asked multiple questions, we will solve the first question for you. If you want any…

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

Q: Types of Forecasts that might be needed in IKEA

A: Let’s first understand the meaning of Forecasting and types of Forecasting. Forecasting can be…

Q: our manager is trying to determine what forecasting method to use. Based upon the following…

A: first we put the value on excel sheet then applying weighted moving average formula which shown in…

Q: a) Using a weighted 3-month moving average with weights of 0.60, 0.30, and 0.10, Find the July…

A: Forecasting is a technique used to predict future outcomes on the basis of past data. In businesses…

Q: Explain the distinction between short- and long-term forecasts?

A: Forecasting is a technique that enables the generation of educated forecasts by utilising historical…

Q: Explain the nature of forecasting when it's periods are farthest into the future in forecasting ?

A: To be determined: the nature of forecasting when it's periods are farthest into the future in…

Q: Air travel on Mountain Airlines for the past 18 weeks was:Week Passengers1 4052 4103 4204 4155 4126…

A: a) The moving average technique would not be appropriate for the given data because the data is…

Q: Your manager is trying to determine what forecasting method to use. Based upon the following…

A: In exponential smoothing, the smoothing constant is used to forecast the demand for the next period…

Q: snip

A: A moving average forecast becomes less responsive to change in a data series when more data points…

Q: Use = 0.2 to compute the exponential smoothing values for the time series. Forecast for Month 8. The…

A: Given that , Forecast for 6 months is 21 The two month moving average for months two to five is…

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

A: ANSWER IS AS FOLLOWS:

Q: a. Compare a three-month moving average forecast with an exponential smoothing forecast. Use a =…

A: Below is the solution:-

Q: Use Excel to solve the below problems. 1. Construct an exponential forecasting calculator to find…

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

Q: Use the following information to compute a single exponential smoothing model forecast with a…

A: From the above information, Let, Forecast for period 1 =f1 =115 Actual value for period 1 =a1…

Q: Explain why such forecasting devices as moving averages, weighted moving averages, and exponential…

A: Forecasting is the anticipating the future demand considering the historical data. Following are the…

Q: a. Calculate the simple three-month moving average forecast for periods 4 to 12.

A: Since you have asked multiple questions, we will solve the first question for you. If you want any…

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

Use exponential smoothing with a=0.2 and a=0.5 to generate forecasts for periods 2 through 6. Use MAD and MSE to decide which of the two models produced a better forecast.

Period Actual Forecast

1 15 17

2 18

3 14

4 16

5 13

6 16

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

Trending now

This is a popular solution!

Step by step

Solved in 2 steps with 2 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_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.
Under what conditions might a firm use multiple forecasting methods?
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 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 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_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 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.