Answered: Based on this information, what…

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Statistics

Based on this information, what percentage of the variation in overhead costs is explained by the independent variable?

Algebra and Trigonometry (MindTap Course List)

4th Edition

ISBN:9781305071742

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section1.FOM: Focus On Modeling: Fitting Lines To Data

Problem 12P: Demand for Candy Bars In this problem you will determine a linear demand equation that describes the...

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Demand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00
Midgett Co. has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff suggested that linear regression be employed to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis are as follows: Month MaintenanceCost Machine Hours Jan. $ 5,040 620 Feb. 3,648 420 Mar. 4,320 520 Apr. 3,331 390 May 5,221 650 June 3,550 400 July 3,655 430 Aug. 5,365 690 Sept. 5,110 640 Oct. 4,866 610 Nov. 3,944 460 Dec. 3,790 440 Sum $ 51,840 6,270 Average $ 4,320.00 522.50 Average cost per hour ($51,840/6,270) = $8.27 (rounded to the nearest cent)r = 0.99821r2 = 0.99780The percent of the total variance that can be…
Midgett Co. has accumulated data to use in preparing its annual profit plan for the upcoming year. The cost behavior pattern of the maintenance costs must be determined. The accounting staff suggested that linear regression be employed to derive an equation for maintenance hours and costs. Data regarding the maintenance hours and costs for the last year and the results of the regression analysis are as follows: Month MaintenanceCost Machine Hours Jan. $ 5,000 600 Feb. 3,644 440 Mar. 4,400 610 Apr. 3,337 480 May 5,222 660 June 3,390 410 July 3,618 470 Aug. 5,384 630 Sept. 5,114 590 Oct. 4,883 590 Nov. 3,925 430 Dec. 3,850 350 Sum $ 51,767 6,260 Average $ 4,313.92 521.67 Average cost per hour ($51,767/6,260) = $8.27 (rounded to the nearest cent) r = 0.85977 r2 = 0.73920 The percent of the total variance that…
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c. E Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 5304.4 + (0.0219) × Billable Hours +1 (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly overhead costs and billable hours data Overhead Costs Billable Hours O IT $385,000 3,000 $430,000 4,000 $460,000 5,000 $511,000 6,000 $580,000 7,000 $600,000 8,000 Print Done
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through o. Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs OxBillable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly Overhead Costs and Billable Hours Data Overhead Costs $385,000 Billable Hours 3,000 $425,000 4,000 $445.000 5,000 $497,000 6,000 $570,000 7,000 $590,000 8,000
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Mark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of stereo speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for their particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 10 years and was reduced to the data that follow: YEAR SALES/UNIT (THOUSANDS) PRICE $/UNIT ADVERTISING ($000) 1998 395 278 605 1999 695 219 831 2000 895 216 1,104 2001 1,286 207 1,404 2002 1,147 219 1,203 2003 1,180 193 1,286 2004 895 222 884 2005 1,104 202 1,104 2006 974 220 696 2007 1,238 216 884 2008 884 220 696 2009 804 247 696
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 247733.3 +(43.2000) x Billable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) b. 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, bo. if appropriate. Choose the correct answer below. OA. The value of by is the predicted overhead costs for 0 billable hours. OB. For each increase of 1 unit in overhead costs, the predicted billable hours are estimated to increase by bo OC. It is not appropriate to interpret by. because its value is the predicted…
You have to examine the relationship between the age and price for used instrument sold in the last year by a company. Here is the table of the data: a. Determine the degree of relationship between in instument’s age and the price. b. Identify the equation of linear regression. c. How much will a used instrument worth after 6 years? 12 years? 15 years? d. Explain the predicting capability of the equation.
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What needs to change in an overall problem if one wants to use linear regression?