Answered: Develop Linear Regression Model.…

Develop Linear Regression Model. Forecast sales for 8, 14 and 17 years of education. Sales(1000s) Years of Education 24 10 18 9 20 11 22 6 26 13 23 16 21 18

Marketing

20th Edition

ISBN:9780357033791

Author:Pride, William M

Publisher:Pride, William M

Chapter6: Target Markets: Segmentation And Evaluation

Section: Chapter Questions

Problem 17DRQ: Under what conditions might a firm use multiple forecasting methods?

See similar textbooks

Related questions

Q: Using a four-month moving average, determine the two-step-ahead forecast for Julythrough December…

A: Two-step four month moving average forecast for July to December, 2013.

Q: The following gives the number of accidents that occurred on Florida State Highway 101 during the…

A: Given data - Month January February March April No. of Accidents 30 40 60 95

Q: The following data are for calculator sales in units at anelectronics store over the past 9 weeks:…

Q: 2. What is the Mean Absolute Deviation (MAD)? 3. Use the following set of data to calculate the Mean…

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

Q: 1. The department manager using a combination of methods has forecast sales of toasters at a local…

A: The answer is as below: WE ARE ALLOWED TO DO ONE QUESTION ONLY AT AT TIME.

Q: The following table shows the past two years of quarterly sales information. Assume that there are…

A: Quarter Sales 1 154 2 190 3 154 4 145 5 216 6 236 7 208 8 175

Q: Room registrations in the Toronto Towers Plaza Hotel have been recorded for the past 9 years. To…

A: Given Data:

Q: The following gives the number of accidents that occurred on Florida State Highway 101 during the…

A: Given-

Q: List of specific weakness of each of these approaches to developing a forecast. a. Consumer…

A: a) Consumer Surveys: Consumer survey is a type of source to get information about the satisfaction…

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: he following data were collected during a study of consumer buying patterns: Observation x…

A: Given that: Observation x y 1 19 72 2 21 81 3 43 79 4 28 81 5 56 98 6 49 96 7 32 82…

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: Three

A: Exponential smoothing Exponential smoothing use the formula as given below to forecast for time…

Q: Describe what "prediction" means for forecasting models.

A: Forecasting is the process of predicting the future demand according to the previous data and…

Q: 3. Weighted Moving Averages Model: Use 40% weight for the most recent data, 35% weight for the…

A: Given data is Weight 40% for most recent data, 35% for the 2nd most recent data, and 25% for the…

Q: Q5: The following data represent the sales of the National Tigers Company for the period from…

Q: Given the data below, what is the simple linear regression model that can be used to predict sales…

A: A statistical technique for predicting the value of one variable based on the value of another is…

Q: List the specific weaknesses of each of these approaches to developing a forecast:a. Consumer…

A: Forecasting is the process of identifying the demand accurately for future production planning and…

Q: Rhonda Clark, a Slippery Rock, Pennsylvania, realestate developer, has devised a regression model to…

A: a) y = 13473 +37.65(1860) =$83502

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: Assume you have noted the following prices for paperback books and the number of pages that each…

Q: GHM Company is a well-known automotive company in the United States. GHM has tracked the monthly…

A: Find the Given details below: Given details Year Quarter 1 2 3 4 1 0.8565 1.0558 2…

Q: What is the first-order smoothing and trend adjusted smoothing?

A: Smoothing data is the term which described as the one that removes the variation as well as states…

Q: The table below shows the violent crime rate in Canada between 1977 and 2004. a. Enter this data…

A: Quadratic regression equation is of form ax2+bx+c where a should not be equal to zero.

Q: 1. The number of bushels of apples sold at a roadside fruit stand over a 12-day period were PROBLEMS…

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

Q: A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales…

A: As there are deviation in both side of the trend-line, it is concluded that trend-adjusted…

Q: Community Federal Bank in Dothan, Alabama, recently increased its fees to customers who use…

A: Using trend projection with regression to forecast usage for weeks 13–16.

Q: Quarterly sales of a local department store over a 4-year period are given below: Quarters Sales (in…

A: Given Information: Year Quarter1 Quarter2 Quarter3 Quarter4 2016 500 490 570…

Q: Consider the following time series. Quarter Year 1 Year 2 Year 3 70 67 61 48 40 50 3 57 59 52 4 77…

A: As requested, I have solved the (b) and (c) part. Kindly refer to Step 2 and 3 for the solution.

Q: A producer of picture frames uses a tracking signal withlimits of ± 4 to decide whether a forecast…

A: Mean Absolute Deviation:The sum of small mistakes is used to evaluate forecasting algorithms. By…

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: 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: Suppose these data show the number of gallons of gasoline sold by a gasoline distributor in…

A: Given data is

Q: Quarterly sales of a local department store over a 4-year period are given below: Quarters 2016 Q1…

A: Formula:

Q: Trail Questions National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a…

A: Find the Given Details below: Given Details: Month Sales ('000 Units) Feb 19 Mar 18 Apr…

Q: The following data are for calculator sales in units at an electronics store over the past nine…

A: Given Sales data-

Q: What is differ from SMA (Simple moving average), WMA (Weighted moving average), SLR (Single linear…

A: AnswerCurrent prices are those prices on which the goods and services are sell and purchased in the…

Q: Quarter 1 2 3 1 11 14 17 2 20 23 26 3 29 32 35 4 38 41 44 Compute seasonal relatives for this…

Q: Two independent methods of forecasting based on judgment and experience have been prepared each…

A: Given data Month Sales Forecast1 Forecast 2 1 770 771 769 2 789 785 787 3 794 790 792…

Q: Community Federal Bank in Dothan, Alabama, recently increased its fees to customers who use…

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

Q: c) What is the MSE? 4.16 Refer to Solved Problem 4.1 on page 144. a) Using the trend-projection…

A: First, we calculate the slope and intercept by using the formulas below.

Q: The number of bushels of apples sold at a roadside fruit stand over a 12-day period were as follows:…

A: Since you have asked a question with multiple subparts, we will answer the first three subparts for…

Q: What benefits would exponential smoothing have over moving averages as a prediction too

A: The benefits of the exponential smoothing over moving averages with respect to the prediction tool…

Q: The following data come from regression line projections: Compute the MAD and MSE.

Q: State what is a qualitative forecasting model and it uses under forecasting

A: To be determined: what is a qualitative forecasting model and it uses under forecasting

Q: An additive Holt-Winters forecast is being performed on accounting industry revenue data. Revenue…

A: Find the given details below: Given details: Date Time Revenue($ billions) lt bt st Forecast…

Q: Community Federal Bank in Dothan, Alabama, recently increased its fees to customers who use…

A: Trend projection with regression is a typical forecasting method in which relationship between…

Q: 3. National Mixer, Inc., sells can openers. Monthly sales for a seven-month period were as follows:…

A: Note: - Since we can answer only up to three subparts we will answer the first three subparts (a, b…

Q: (i) Obtain the trend projection with regression forecast.

A: The answer is as below:

Concept explainers

Forecasting

Forecasting is a methodology that uses historical data as inputs to make well-informed predictions about the course of future trends. Forecasting is the method of making forecasts based on historical and current data, most commonly by trend analysis. In the business world, forecasting is a basic statistical task. Forecasting is used by businesses to decide how to allocate their budgets or prepare for expected expenditures in the future. Forecasts help managers formulate and execute production plans by providing forecasts. The primary goal of forecasting is to make accurate predictions.

Question

Develop Linear Regression Model.

Forecast sales for 8, 14 and 17 years of education.

Sales(1000s) Years of Education

24 10

18 9

20 11

22 6

26 13

23 16

21 18

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 5 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 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?
Management of a home appliance store wants to understand the growth pattern of the monthly sales of a new technology device over the past two years. The managers have recorded the relevant data in the file P13_05.xlsx. Have the sales of this device been growing linearly over the past 24 months? By examining the results of a linear trend line, explain why or why not.
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_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 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?
Management of a home appliance store would like to understand the growth pattern of the monthly sales of Blu-ray disc players over the past two years. Managers have recorded the relevant data in the file P13_33.xlsx. a. Create a scatterplot for these data. Comment on the observed behavior of monthly sales at this store over time. b. Estimate an appropriate regression equation to explain the variation of monthly sales over the given time period. Interpret the estimated regression coefficients. c. Analyze the estimated equations residuals. Do they suggest that the regression equation is adequate? If not, return to part b and revise your equation. Continue to revise the equation until the results are satisfactory.
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 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.
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?
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.
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?