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Test the significance of the correlation coefficient calculated in question 2 (below) at α = 0.05. Use the steps in conducting hypothesis tests. Question 2:  The Pearson r Correlation Coefficient: r = 0.998 The equation of the regression line: y = 1.81x + -1.7 The purpose of calibration in this application is to estimate pressure from an observed scale reading. Estimate the pressure for a scale reading of 54: Pressure = 99.44lb/sq. in

Test the significance of the correlation coefficient calculated in question 2 (below) at α = 0.05. Use the steps in conducting hypothesis tests. Question 2:  The Pearson r Correlation Coefficient: r = 0.998 The equation of the regression line: y = 1.81x + -1.7 The purpose of calibration in this application is to estimate pressure from an observed scale reading. Estimate the pressure for a scale reading of 54: Pressure = 99.44lb/sq. in

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Test the significance of the correlation coefficient calculated in question 2 (below) at α = 0.05. Use the steps in conducting hypothesis tests.

Question 2: 

The Pearson r Correlation Coefficient: r = 0.998

The equation of the regression line: y = 1.81x + -1.7

The purpose of calibration in this application is to estimate pressure from an observed scale reading. Estimate the pressure for a scale reading of 54: Pressure = 99.44lb/sq. in


SUM PRESSURE, X 10 10 10 10 10 50 50 50 50 50 300 Scale Reading. y 13 18 16 15 20 86 90 88 88 92 526 xy 130 180 160 150 200 4300 4500 4400 4400 4600 23020 x² 100 100 100 100 100 2500 2500 2500 2500 2500 13000 y² 169 324 256 225 400 7396 8100 7744 7744 8464 40822
Transcribed Image Text:SUM PRESSURE, X 10 10 10 10 10 50 50 50 50 50 300 Scale Reading. y 13 18 16 15 20 86 90 88 88 92 526 xy 130 180 160 150 200 4300 4500 4400 4400 4600 23020 x² 100 100 100 100 100 2500 2500 2500 2500 2500 13000 y² 169 324 256 225 400 7396 8100 7744 7744 8464 40822
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