Solve the problem.The data in the table represent the amount of raw material (in tons) put into an injectionmolding machine each day (x), and the amount of scrap plastic (in tons) that is collected fromthe machine every four weeks (y). Also shown below are the outputs from two differentstatistical technologies (TI-83/84 Calculator and Excel). A scatterplot of the data confirmsthat there is a linear association. Report the equation for predicting scrap from raw materialusing words such as scrap, not x and y. State the slope and intercept of the predictionequation. Round all calculations to the nearest hundredth.Xy2.713.612.33 2.802.33 2.772.212.342.11 2.152.082.061.981.951.841.842.021.951.731.68LinRegy=a+bxa = -2.376991175b=2.192699333r² =.9806834986P = .9902946524InterceptX Variable 1Coefficients-2.3769911752.192699333scrap = 2.19 -2.38(raw material); slope = 2.19 and the intercept is -2.38.,scrap = -2.38 + 2.19(raw material); slope = -2.38 and the intercept is 2.19.scrap = -2.38 + 2.19(raw material); slope = 2.19 and the intercept is -2.38.scrap = 2.19 2.38(raw material); slope = -2.38 and the intercept is 2.19.

regression equation : y = a+bxa = -2.38b = 2.19x = raw materialy = scrap

Answered: Solve the problem. The data in the…

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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