Here is a bivariate data set. Find the regression equation for the response variable y.y73.659.680.651.682.471.382.845.476.860.675.167.580.562.181.661.185.532.380.949.680.634.8regression equation:Enter the equation in slope-intercept form with parameters accurate to three decimal places.

The data contains x and y variables.

Answered: Here is a bivariate data set. Find 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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The correlation between first year college GPA and high school GPA is 0.683. If a simple linear regression was conducted to predict first year college GPA from high school GPA what does the correlation tell us about the fit of the model?
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.3 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) 7.8 175 7.3 9.5 274 7.4 156 9.9 294 9.2 183 256 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... The regression equation is y =+x. (Round to one decimal place as needed.)
Here is a bivariate data set. Find the regression equation for the response variable y. x y 60.9 36.2 55.8 44.3 27.8 61.7 36.1 56.3 56 53.7 49.8 55.2 45.7 51.5 60.1 46.6 63.1 50 63.9 40.2 68.8 45.4 32.3 60.4 76.6 40.6 65.4 46 65.6 42.7 regression equation: Enter the equation in slope-intercept form with parameters accurate to three decimal places.
Run a regression analysis on the following bivariate set of data with y as the response variable. x y -9.7 -66.2 5.6 28.3 -4.5 11.9 35.6 94.9 15.7 21.1 30.8 86.3 48.7 127.9 13 57.3 35.3 109 23.6 32.4 58 166.3 28.1 64.4 19.1 51.5 25.6 53.3 46.1 186.4 43.5 128 Predict what value (on average) for the response variable will be obtained from a value of 14.8 as the explanatory variable. Use a significance level of α=0.05 to assess the strength of the linear correlation.What is the predicted response value? y =
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The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression eqation, using the first variable (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140. Use a significance level of x Systolic Diastolic 116 82 124 88 112 72 144 95 138 96 112 76 145 88 124 76 130 90 129 94 1)Find the correlation coefficient. 2)State the appropriate critical r value to use to test the claim that the correlation between systolic blood pressure and diastolic blood pressure is significantly different from 0 3)The correlation between diastolic blood pressure and systolic blood pressure is: significant, not significant, weak, none 4)The best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140 is closest to 1pts
Run a regression analysis on the following bivariate set of data with y as the response variable. y 56.3 -257.6 14.5 670.8 49.4 431 60.7 200.3 60.1 70.3 52.6 -162.4 46.2 -406.9 45.1 -3.6 39.6 292.4 51.2 274.8 53.1 -77.4 50 496.6 46.9 251.5 48.5 -188.7 79.8 233 33.5 -415.6 49.2 431.3 download link provided here: Download CSV Predict what value (on average) for the response variable will be obtained from a value of 32.1 as the explanatory variable. Use a significance level of a = 0.05 to assess the strength of the linear correlation. What is the predicted response value? y = 169.94127 (Report answer accurate to one decimal place.)

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