An important application of regression analysis is in the estimation of cost. Bycollecting data on volume and cost and using the least squares method todevelop an estimated regression equation relating volume and cost, one canestimate the cost associated with a particular manufacturing volume. Considerthe following sample of monthly production volumes and total costs data for amanufacturing operation for the year 2018.MonthProduction Volume (units)Total Costs ($)January 2018February 20185006,0003504,000March 20184505,000April 20185505,400May 20186005,900June 20184004,000July 2018August 2018September 20184004,2003503,9004004,300October 20186006,000November 20187006,400December 20187507,000Which of the following is NOT necessarily true about the interpretation of thevalue of b in the simple linear regression equation y = a + bx for this problem? *I.The monthly total costs will increase by $7.6437 for every one-unit increase in theproduction volume.I.Since b >0, there is a direct relationship between production volume and totalcosts.III.Because b> 1, there is a very strong positive linear relationship betweenproduction volume and total costs.i and ii onlyO ii onlyO ii onlyO ii and ii onlyIIооо

The regression equation is in the form of straight line y = a + bx where y =…

Answered: Which of the following is NOT…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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1. Sue is conducting a regression analysis to predict the amount of salaries expense using the number of employees and the average rate of pay. This type of regression analysis is called a(n) independent regression. linear regression. multiple regression. dependent regression.
The below data on the production volume x and total cost y (in dollars) for a particular manufacturing operation were used to develop the estimated regression equation y = 1,217.33 + 7.68x. Production Volume Total Cost ($) $ (units) 400 Submit Answer 450 550 600 700 750 4,100 4,900 5,400 5,900 6,500 (a) The company's production schedule shows that 650 units must be produced next month. What is the point estimate of the total cost (in dollars) for next month? (Round your answer to the nearest cent.) $6209.33 7,000 (b) Develop a 99% prediction interval for the total cost (in dollars) for next month. (Round your answers to the nearest cent.) X to $ X (c) If an accounting cost report at the end of next month shows that the actual production cost during the month was $6,700, should managers be concerned about incurring such a high total cost for the month? Discuss. Since $6,700 is within the prediction interval, managers should not be concerned about Incurring such a high total cost for one…
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Situation: The Ipod Touch has been out for two years now and a lot of data has been collected.Relevant Relationship:There is a functional relationship between Price of an IPod Touch,� and Weekly Demand,�.Below is a table of data that have been collected Price,�,($) Weekly Demand,�,(1,000s) 150 207 170 199 190 198 210 185 230 181 250 169 A.. Find the linear model that best fits this data using regression and enter the model below(for entry round the linear parameter value to nearest 0.01 and constant parameter to nearest 1)�=�(�)= B. The squared correlation coefficient �2 was 0.95(note: values less than 0.95 MAY mean the model is not appropriate for making predictions)Now answer these two questions using the UNROUNDED model parametersC. What does the model predict will be the weekly demand if the price of an ipod touch is $184 ? (nearest 100)D. According to the model at what should the price be set in order to have a weekly demand of 176,200 ipod Touches? $…
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Situation: The Ipod Touch has been out for two years now and a lot of data has been collected.Relevant Relationship:There is a functional relationship between Price of an IPod Touch,� and Weekly Demand,�.Below is a table of data that have been collected Price,�,($) Weekly Demand,�,(1,000s) 150 217 170 206 190 191 210 185 230 182 250 170 A.. Find the linear model that best fits this data using regression and enter the model below(for entry round the linear parameter value to nearest 0.01 and constant parameter to nearest 1)�=�(�)= B. The squared correlation coefficient �2 was 0.95(note: values less than 0.95 MAY mean the model is not appropriate for making predictions)Now answer these two questions using the UNROUNDED model parametersC. What does the model predict will be the weekly demand if the price of an ipod touch is $219 ? (nearest 100)D. According to the model at what should the price be set in order to have a weekly demand of 171,300 ipod Touches? $…
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A biologist is interested in predicting the percentage increase in lung volume when inhaling (y) for a certain species of bird from the percentage of carbon dioxide in the atmosphere (x). Data collected from a random sample of 20 birds of this species were used to create the least-squares regression equation ŷ = 400-0.08x. Which of the following best describes the meaning of the slope of the least-squares regression line? (A) The percentage increase in lung volume when inhaling increases by 0.08 percent, on average, for every 1 percent increase in the carbon dioxide in the atmosphere. (B) The percentage of carbon dioxide in the atmosphere increases by 0.08 percent, on average, for every 1 percent increase in lung volume when inhaling. (C) The percentage increase in lung volume when inhaling decreases by 0.08 percent, on average, for every 1 percent increase in the carbon dioxide in the atmosphere. (D) The percentage of carbon dioxide in the atmosphere increases by 0.08 percent, on…
Suppose that a simple linear regression model is appropriate for describing the relationship between y = house price (in dollars) and x = house size (in square feet) for houses in a large city. The population regression line is y = 22,500 + 43x and ?e = 4,000. b) Approximately what proportion of 2,000 sq ft homes would be priced over $110,000? (You may need to use a table. Round your answer to four decimal places.) Approximately what proportion of 2,000 sq ft homes would be priced under $100,000? (You may need to use a table. Round your answer to four decimal places.)
A linear regression analysis reveals a strong, negative linear relationship between x and y. Which of the following could possibly be the results from this analysis? (A) ŷ 13.1 27.4x, r = 0.85 (B) == 27.4+ 13.1x, r = -0.95 (D) == (C) ŷ 13.1+ 27.4x, r = 0.95 542 385x, r = -0.15 (E) 0.85 0.25x, r = -0.85

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