Based on the data shown below, calculate the regression line (each value to two decimal places)y =y16.356.17.6217.098.18.169.21.131022.51119.771222.341323.111424.781524.05寸|

Answered: Image /qna-images/answer/af96077e-c78a-4b23-8845-1822ef05a778.jpg

Answered: Based on the data shown below,…

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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Annual high temperatures in a certain location have been tracked for several years. Let X represent the year and Y the high temperature. Based on the data shown below, calculate the regression line (each value to two decimal places). y = X + y 5 18.35 16.44 7 17.43 8 17.32 9 18.51 10 18.8 11 15.59 12 15.88 13 17.47 14 17.56 15 15.55 16 18.74 17 17.83 18.12 19 15.41 20 18.7 Question Help: DVideo O 00
Run a regression analysis on the following bivariate set of data with y as the response variable. x y 58.3 81.3 77.7 48.5 49.3 67.2 68.5 58.9 46.4 93.1 65.5 75.8 48.9 90.5 65.2 66.9 63.2 79.4 56.5 89.3 65.6 75.5 40.4 96.2 Find the correlation coefficient and report it accurate to three decimal places. r = What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to one decimal place. (If the answer is 0.84471, then it would be 84.5%...you would enter 84.5 without the percent symbol.)r² = %Based on the data, calculate the regression line (each value to three decimal places)y = x + Predict what value (on average) for the response variable will be obtained from a value of 77.8 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? (Report answer accurate to one decimal place.)y =
Based on the data shown below, calculate the regression line. y 21.13 5 21.96 7 20.29 8 19.92 9 17.55 10 18.78 11 17.11 12 15.64 13 14.17 14 14.5 y = X + [three decimal accuracy] [three decimal accuracy]
Run a regression analysis on the following bivariate set of data with y as the response variable. x y 43.2 -8.5 114.8 171 73.3 87.5 58.4 57.9 68.2 37.2 70.6 90.4 61.4 82.1 87.1 79.6 58 -9.2 78.4 77.2 80.5 87.3 64.1 22.9 54.3 32 Verify that the correlation is significant at an α=0.05α=0.05. If the correlation is indeed significant, predict what value (on average) for the explanatory variable will give you a value of 20.7 on the response variable.What is the predicted explanatory value?x = (Report answer accurate to one decimal place.)
Run a regression analysis on the following bivariate set of data with y as the response variable. y 62.8 75.2 60 70.4 59.8 63 59.3 68.5 59 70.3 52.4 50.8 63.4 61.9 70.3 68.1 65.6 69.3 56.8 60.9 67.5 77.5 55.5 57.2 Find the correlation coefficient and report it accurate to three decimal places. What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to one decimal place. (If the answer is 0.84471, then it would be 84.5%...you would enter 84.5 without the percent symbol.) r2 = Based on the data, calculate the regression line (each value to three decimal places) y = Predict what value (on average) for the response variable will be obtained from a value of 52.5 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? (Report answer accurate to one decimal place.) y = Submit Question IO 01 100 O Details
Based on the data shown below, calculate the regression line (each value to two decimal places) y = X + Enter an integer or decimal number [more..] X y 18.66 20.18 5 21.4 6 22.22 7 21.44 8 23.56 9 22.28 10 22.6 3 4
Based on the data shown below, calculate the regression line (each value to two decimal places)y = x y 2 17.72 3 19.58 4 21.24 5 22.6 6 25.56 7 28.62 8 30.78 9 31.74 10 36.4 11 35.96 12 38.62 13 42.18 14 43.14
Run a regression analysis on the following bivariate set of data with y as the response variable. x y 34.4 51.4 21.3 55.8 42.1 45.1 46 44.3 16.6 64 45.5 45.9 41.8 38.8 20.8 56.6 27.6 52.9 12 66.2 35.6 52.4 21.6 57.4 Predict what value (on average) for the response variable will be obtained from a value of 36.9 as the explanatory variable. Use a significance level of α=0.05α=0.05 to assess the strength of the linear correlation.What is the predicted response value?y = (Report answer accurate to one decimal place.)
Based on the data shown below, calculate the regression line (each value to two decimal places) %3D y 13.28 13.41 13.94 8. 10.37 9. 13.7 10 11.03 11 12.46 12 9.99 13 8.82 14 10.55 15 9.18 16 9.81 17 9.84 18 9.47 19 9.2 670
Run a regression analysis on the following bivariate set of data with y as the response variable. x y 57.9 -34.4 16.6 92 40.1 89 55.8 54.5 57.9 27.4 17.3 164.1 65.2 62.4 48.3 51.9 66.2 14.5 70.9 -39.2 57 -90.1 58.5 63 Find the correlation coefficient and report it accurate to three decimal places.r = What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to one decimal place. (If the answer is 0.84471, then it would be 84.5%...you would enter 84.5 without the percent symbol.)r² = %
Write out the regression equation using the information from the table: Variable Est. S.E. t p-value 95% Confidence Interval Race 5.20 1.05 Party 7.54 0.14 7.26, 7.82 Income 0.31 0.65 0.48 -0.96 , 1.58 Intercept 15.00 1.13 13.31 0.000 12.77, 17.18
Run a regression analysis on the following data set with y as the response variable. x y 86.9 31.3 54.8 1.8 87.8 20.1 79.7 25.1 101 41 83 24.2 68.7 28.6 86.7 35.6 93.8 33.6 What is the predicted value of the response variable when the explanatory variable has value 78.87 Round your final answer to 1 decimal place.

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Based on the data shown below, calculate the regression line (each value to two decimal places) y 16.35 6. 17.62 7 17.09 8 18.16 21.13 10 22.5 11 19.77 12 22.34 13 23.11 14 24.78 15 24.05