Millie wants to install a new carpet in the living room of her house. She calculated the square footage of the room and then multiplied it by a set cost factor to estimate the cost. This is an example of_________ Group of answer choices Parametric estimating Three-point estimating Bottom-up estimating Analogous estimating

Millie wants to install a new carpet in the living room of her house. She calculated the square footage of the room and then multiplied it by a set cost factor to estimate the cost. This is an example of_________ Group of answer choices Parametric estimating Three-point estimating Bottom-up estimating Analogous estimating

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 40P: The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels....

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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?
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.
Selection and employment of the correct estimation method is: Multiple Choice O O O Easy once the data is gathered. Relatively easy because only two effective methods exist. Dependent on the accuracy/cost tradeoff for the estimation objectives. Primarily subjective in nature. Difficult because so many effective methods are available.
As employees leave a company, they are asked to rate their level of job satisfaction during the time they were employed by the company. A sample set of scores (out of a maximum of 10) is provided below. 3 6 4 4 5 2 1 3 2 5 3 7 2 2 3 1 9 1 Use the information provided in the table to calculate: The median; The mode; The mean; The lower quartile (Q1); The upper quartile (Q3); The interquartile range (IQR); The standard deviation. State whether or not the ex-employees were likely to have left the company as a result of lack of job satisfaction. Use the statistics above to justify your conclusion. Discuss in which ways the company could benefit from making these statistics available to its current employees.
Interpret the coefficients of your regression model. Specifically, what does the fixed component of the model mean to the consulting firm? Interpret the fixed term, b 0b0, if appropriate. Choose the correct answer below. A. It is not appropriate to interpret b 0b0, because its value is the predicted billable hours for overhead costs of 0 dollars, but the firm cannot have overhead costs of 0 dollars associated with a client. B. The value of b 0b0 is the predicted overhead costs for 0 billable hours. C. It is not appropriate to interpret b 0b0, because its value is the predicted overhead costs for 0 billable hours, but someone with 0 billable hours would not actually be a client of the firm. D. For each increase of 1 unit in billable hours, the predicted overhead costs are estimated to increase by b 0b0. E. The value of b 0b0 is the predicted billable hours for an overhead cost of 0 dollars. F. For each increase of 1 unit in…
(a) Assuming that a simple linear regression model is appropriate, obtain the least squares fit relating selling price to taxes paid. What is the estimate of o²? (b) Find the mean selling price given that the taxes paid are x = 7.50. (c) Calculate the fitted value of y corresponding to x = 5.8980. Find the corresponding residual.
You work as a sales operations analyst in a company that makes 3D printers. Your manager has asked you to determine if a salesperson's sales volume (in terms of the number of 3D printers they sell in a year) depends on the number of client calls they make. After analyzing past data and creating a linear regression model, you've found the following relationship: No. of printers sold = 18.47 + 1.13 times the number of client calls. 1. Based on this, how many client calls will a salesperson need to make to sell 245 printers next year? a. 200 (rounds to) b. 215 (rounds to) c. 230 (rounds to) d. 240 (rounds to)
Explain the compromise between responsiveness and stability in a predictive system using data from time series.
The president of a small manufacturing firm is concerned about the continual growth in manufacturing costs in the past several years. The data series of the cost per unit for the firm’s leading product over the past eight years is as follows: Year Cost/Unit ($) Year Cost/Unit ($) 1 20.00 5 26.10 2 25.00 6 30.60 3 29.10 7 32.20 4 27.10 8 36.20 Choose the correct graph for the time series and linear trend. The correct graph is . A. B. C. D. Use Excel to develop a simple linear regression model for these data. What average cost increase has the firm been realizing per year? Do not round intermediate calculations. Round your answers to four decimal places. The regression equation is Unit Cost = + Year. The average cost increase per year is $ .
Use the below formula to calculate the CLV for the following: A manager of a cable company wants to determine if it is strategic to acquire the Brett family, by estimating their household-level CLV. The manager estimates that it will cost the company $80 (A) to get the Bretts’ to switch, and the Bretts’ will generate $150 profit each year (M), with a $30 annual marketing cost to retain them (C). The estimated retention rate (r) is 65%, and the current discount rate is 5%.(d) i) CLV= ii) Based on your calculation, are the Brett’s profitable to the cable company?
General Motors would like an estimate of the chance that Tesla will bring the cost of batteries down from $300 per kWh to $70. Dr. Tetlock has developed a process whereby selected teams are better estimators of future probabilities than experts, General Motors is willing to pay Dr. Tetlock for his teams' O scenarios O contingency plans O forecasts