Answered: A company sells wielding generators.…

A company sells wielding generators. The demand for periods 1 to 9 is 44,52,50,,54,55,55,60, 56 and 62. Develop a regression forecasting equation and forecast sales for period 15

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: Both time series and causal forecasting assume that the past relationship between demand and the…

A: Time series forecasting refers to the prediction of future events of a business. According to the…

Q: The data shown in the following table represent visitors to the Hawaiian Islands over the past…

A: Find the Given details for Seasonal and trend factors: Given details: Visitors Quarter…

Q: Consider the following set of time series sales data for a growing company over the past 8 months:…

A: The time series plot shows a horizontal pattern.

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: 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: 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: Sales of tablet computers at Ted Glickman's electronics store in Washington, D.C., over the past 10…

A: Error = Actual - Forecast Absolute Error = Positive Difference of Actual Demand and Forecast…

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: The number of heart surgeries performed at Heartville General Hospital has increased steadily over…

A: Since you have submitted a question with multiple sub-parts as per guidelines we have answered the…

Q: Using an exponential smoothing model with an alpha value of 0.20, estimate the smoothed value…

A: The answer is as below:

Q: The manager of a travel agency has been using a seasonally adjusted forecast to predict demand for…

A: ANSWER IS AS BELOW:

Q: Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the…

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: Exponential smoothing is used to forecast automobile battery sales. Two value of a are examined, a =…

A: Given information:

Q: Period 1 2 3 4 6. 7 8 9 10 11 12 Sales 568 604 645 742 661 606 749 680 704 736 660 756

Q: The demand (in number of units) for Apple iPad over the past 6 months at BestBuy is summarized…

A: 2-month weighted moving average: Formula: Answer:

Q: 1. Consider the total production (and sales) of ice cream in Canada (in millions of liters) for the…

A: We are authorized to answer three subparts at a time since you have not mentioned which part you are…

Q: 9. a. Obtain the linear trend equation for the following data on new checking accounts at Fair Sav…

A: A trend line is a finest fit straight-line cast-off through liner data sets which support to…

Q: Lori Cook has developed the following forecasting model: ^y=45.0+4.20x,…

A: Using the given Forecasting model the forecast for air conditioner at various level of temperature…

Q: The data below represents the quarterly changes in demand for a product over the next 3 months.…

A: Given data is

Q: A manufacturer of printed circuit boards uses exponentialsmoothing with trend to forecast monthly…

A: The image given in step 2 gives a detailed solution of the question that has been asked.

Q: George kyparisis owns a company that manufactures sailboats. Actual demand for Georges's sailboats…

A: Given data is

Q: Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the…

A: Linear Regression Assume X = Price Y = Number sold X Y XY X2 2.50…

Q: exponential functions for trend data. Assume an initial exponential Forecast of 620 units in period…

A: Below is the solution:-

Q: Two different forecasting techniques (F1 and F2) were used to forecast demand for cases of bottled…

A: Mean Absolute Deviation (MAD) is one of the measures used to summarize historical errors in…

Q: Freight car loadings over an 18-week period at a busy port are as follows: Weeks Loadings (lbs)…

A: Let X denotes the week and Y denotes the number. Now calculate the following:

Q: A coffee shop owner wants to estimate demand for the next four quarters for hot chocolate. Sales…

A: Given, Quarter 1- 1.20 Quarter 2- 1.15 Quarter 3- 0.77 Quarter 4- 0.88

Q: The demand (in number of units) for Apple iPad over the past 6 months at BestBuy is summarized…

A: 2-month weighted moving average: Formula: Answer:

Q: Quarterly demand for Ford F150 pickups at a New York autodealer is forecast with the equation:yn =…

A: Given data Where, X= quarters Yn= Quarterly demand Quarter I of year 1 is 0 Quarter II of year 1…

Q: Weekly demand for dry pasta at a supermarket chain is as follows. Week Demands 1 517 2 510 3 557 4…

A: Forecast for 11 weeks with 5 weighted moving average method. Average of recent 5 data (demand) = D10…

Q: Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the…

A: Price (x) Number Sold (y) xy x2 $2.70 760 2052 7.29 $3.40 515 1751 11.56 $2.10 990 2079 4.41…

Q: A manufacturer of printed circuit boards uses exponential smoothing with trend to forecast monthly…

A: Following formulas are used for calculation: St-1= Average Sales for the month Tt-1=Additional trend…

Q: YEAR 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 ARRIVAL ('000) 35.5 28 30.3 36 49.5 56 72.4…

A: Given information, Year Delayed Rate Arrival X Y 2010 4.2 35.5 2011 3.8 28.00 2012…

Q: My problem asks me to Forecast using a "simple 4-month moving average" but when I calcualte that, I…

A: A) Month Units Sold May 1500 June 1400 July 1800 August 1500…

Q: a. Forecast April through September using a three-month moving average. b. Use simple exponential…

A: Below is the solution:-

Q: Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be…

A: M5TV Appearances(X) Demand for Guitars (Y) XY X2 Y2 3 2 6 9 4 3 5 15 9 25 8 6 48 64 36 5 4…

Q: The Excel file (Forecasting Assignment Data) contains quarterly motorcycle shipments for…

A: Find the Given details below: Given details: Year Quarter Period DemandAt 2000 1 1 49057…

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

A: Linear Regression Month Month ( X ) No. of oil changes ( Y ) XY X2 Jan 1 39 39 1 Feb…

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: Given the Exponential Smoothing Method, Actual Demand alpha = .25 and Forecast Demand alpha = 0.75,…

Q: Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the…

A: a= 0.30 Year Sales Forecast error absolute ES a=0.30 error 1 460 420.00 40 40.00 2…

Q: Using an exponential smoothing model with an alpha value of 0.30, estimate the smoothed value…

A: Below is the solution:-

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: Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the…

A: Given data: X Y 2.60 770 3.60 505 2.00 975 4.20 250 3.10 315 4.00 490 19.50 3305

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: Demand for Soft Shag Month Carpet (1,000 yd.) 1…

A: Exponential smoothing forecast is extension of simple moving average forecast. In exponential…

Q: A concert promoter is forecasting this year's attendance for one of his concerts based on the…

A: Given values, Year Attendance Four years ago 9,000 Three years ago 16,000 Two years ago…

Q: The problem below looks at forecasting methodologies to determine which forecasting model results in…

A: Formulae: For 3 period moving average (SMA) Simple moving average(Ft) = At-1+At-2+At-33Weighted…

Q: The Victory Plus Mutual Fund of growth stocks has had the following average monthly price for the…

A: Note: - Since we can answer only up to three subparts we will answer the first three(1, 2, and 3)…

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 company sells wielding generators. The demand for periods 1 to 9 is 44,52,50,,54,55,55,60, 56 and 62. Develop a regression forecasting equation and forecast sales for period 15

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.

SEE SOLUTION Check out a sample Q&A here

Step 1

VIEW

Step 2

VIEW

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.
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?
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?
Under what conditions might a firm use multiple forecasting methods?
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.
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 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.
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?