The following data represents a report about the x: carbon amount (in mg per 1g steel) and y: the ultimate tensile strength of steel (in MPa): 100 125 125 150 150 200 200 250 | 250 300 300 350 402 406 y 155 142 180 210 190 320 280 400 430 440 390 600 610 670 a. Find the least squares estimate of the regression line with assuming the simple linear regression is valid. (Find the coefficients of the model) b. Write down the probabilistic and deterministic models (equations) with the estimated coefficients. c. Find the sum of squares of the regression and error and their corresponding mean squares. с. d. Test the usefulness of the regression model and the slope of the line of means. e. Find the coefficient of correlation and coefficient of determination of the regression model and interpret your results. е.

The following data represents a report about the x: carbon amount (in mg per 1g steel) and y: the ultimate tensile strength of steel (in MPa): 100 125 125 150 150 200 200 250 | 250 300 300 350 402 406 y 155 142 180 210 190 320 280 400 430 440 390 600 610 670 a. Find the least squares estimate of the regression line with assuming the simple linear regression is valid. (Find the coefficients of the model) b. Write down the probabilistic and deterministic models (equations) with the estimated coefficients. c. Find the sum of squares of the regression and error and their corresponding mean squares. с. d. Test the usefulness of the regression model and the slope of the line of means. e. Find the coefficient of correlation and coefficient of determination of the regression model and interpret your results. е.

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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