An important application of regression in manufacturing is the estimation of cost of production. Based on DATAfrom Ajax Widgets relating cost (Y) to volume (X), what is the cost per widget?DATA:Production Volume (units) Total Cost ($)400 4688450 4893550 5957600 6105700 7111750 7743425 4983475 5461575 6136625 6302725 7538775 7596Question 26 options:None of the answers match my calculation.7.387.548.758.21

1. Understanding the Problem We need to find the cost per widget. The data provided gives the…

Answered: An important application of regression…

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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Weight (lbs.) 173 184 194 214 168 220 188 188 207 167 217 Systolic Blood Pressure 132 143 153 162 154 168 137 149 159 128 166 1. What is the response variable? 2. What is the explanatory variable? 3. What is the equation of the linear regression line? 4. If person's weight is 150, what can we expect the systolic blood pressure to be?
Report the equation of the regression line and interpret it in the context of the problem
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes O and total cost data for a manufacturing operation. O Production Volume (units) Total Cost ($) 400 4100 450 4600 500 5600 600 6400 700 7400 750 8400 N The data on the production volume and total cost y for particular manufacturing operation were used to develop the estimated regression equation ŷ = -524.58+11.66z. a. The company's production schedule shows that 550 units must be produced next month. Predict the total cost for next month. ŷ* = (to 2 decimals) b. Develop a 98% prediction interval for the total cost for next month. X (to 2 decimals) 8 t-value (to 3 decimals) 8pred (to 2 decimals) Prediction Interval for…
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The following data represents the value in 2014 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 245 1000 Boston 370 2100 Chicago White Sox 227 975 Cleveland 207 825 Detroit 254 1125 Houston 175 800 Kansas City 231 700 Los Angeles Angels 304 1300 Minnesota 223 895 New York Yankees 508 3200 Oakland 202 725 Seattle 250 1100 Tampa Bay 188 625 Texas 266 1220 Toronto 226 870 Arizona 211 840 Atlanta 267 1150 Chicago Cubs 302 1800 Cincinnati 227 885 Colorado…
In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. (production is the dependent variable,Independent variable: Price) Dataset: Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103…
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. grams 50 60 70 80 90 100 110 Vitamin C content in mg 9.3 14.3 18.9 23.5 27.5 31.7 36.9 A) Find the regression equation: y = places x + Round your answers to 3 decimal B) Answer the following questions using your un-rounded regression equation. If we test 140 grams of raspberries what is the expected Vitamin C content? nearest tenth) mg (round to the
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. Vitamin C content in mg grams 45 7.3 55 11.5 65 15.9 75 20.3 85 25.8 95 29.2 105 33.9 A) Find the regression equation: y = Round your answers to 3 decimal places B) Answer the following questions using your un-rounded regression equation. If we test 135 grams of raspberries what is the expected Vitamin C content? mg (round to the nearest tenth)
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Total Cost ($) 3900 4700 5300 5700 6400 7100 The data on the production volume and total cost y for particular manufacturing operation were used to develop the estimated regression equation =-490.00 + 10.60x, a. The company's production schedule shows that 450 units must be produced next month. Predict the total cost for next month. ŷ* = * (to 2 decimals) b. Develop a 99% prediction interval for the total cost for next month. (to 2 decimals) 8 t- value decimals) (to 3 * (to 2 Spred decimals) Prediction Interval for an individual Value next month Ⓡ Production Volume…
97000 96000 95000 94000 93000 92000 91000 90000 89000 1000 Revenue vs TV Advertise 2000 3000 4000 5000 6000 97000 96000 95000 94000 93000 92000 91000 90000 89000 Revenue vs Print Advertise 1000 1500 2000 2500 3000 3500 4000 4500 Given above are the plots between weekly gross revenues and TV advertising and between weekly gross revenues and TV advertising for Showtime Movie Theaters. Which advertising (TV or Print) has a stronger relationship with the weekly gross revenues? O A. Print Advertising has stronger relationship with the weekly gross revenue. B. We cannot tell without calculating the related correlation coefficients. O C. TV Advertising has stronger relationship with the weekly gross revenue. O D. The strength of the relationships is the same for both advertising.
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. grams Vitamin Ccontent in mg 65 16.4 75 20.8 85 24.7 95 30 105 34.9 115 39.5 125 43.7 A) Find the regression equation: y=y= x+x+ Round your answers to 3 decimal places B) Answer the following questions using your un-rounded regression equation. If we test 155 grams of raspberries what is the expected Vitamin C content? mgmg (round to the nearest tenth)

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