Here is a bivariate data set. Find the regression equation for the response variable y.Xy77.5-71.420.24837.8142.440.5109.5-7.683.5102.116.8105.1156.620.1111.997.3-18.645.2This dataset can be downloaded as a *.csv file with this link: Download CSVregression equation:70.246.46561.466.567.847.479.557.868.256.155.269.887.364.865.149.160.456.7Enter the equation in slope-intercept form with parameters accurate to three decimal places.

Given : X Y 70.2 77.5 46.4 -71.4 65 20.2 61.4 48 66.5 37.8 67.8 142.4 47.4 40.5…

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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Run a regression analysis on the following bivariate set of data with y as the response variable. X y 9.4 24.2 36.9 66.5 42.6 140.4 -16 -26.1 27.4 52 27.5 71.9 24.8 66.8 21 41.2 33.1 2.4 23.9 34.4 69.2 34.3 71.9 66 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 -13.4 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 =
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.)
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 =
Run a regression analysis on the following bivariate set of data with y as the response variable. X y 9.8 75.6 17.1 50.7 62 71.6 41.4 60.4 44.8 37.7 52.6 40.6 60.1 10.4 55.6 38.9 74.2 -6.6 49.7 33.6 43.9 54.8 Verify that the correlation is significant at an a = 0.05. If the correlation is indeed significant, predict what value (on average) for the explanatory variable will give you a value of 45.9 on the response variable. What is the predicted explanatory value? X =
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.)
Run a regression analysis on the following bivariate set of data with y as the response variable. 58.6 53.6 20 43 24.6 44.1 9.7 40.8 55.1 57.4 -10.3 33.1 39.1 44.9 27.8 48.4 2 33.8 37.6 51.2 52.5 54.3 -12.6 35 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.) 9% 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 53 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 =
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $140 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 39 22 118 67 77 49 124 66 12 64 128 19 6. 147 9. 118 6. 99 75 127 107 95 99 64 109 209 44 8 293 48 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.)
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 = %
Here is a bivariate data set. Find the regression equation for the response variable y. x y 64.9 82.6 69.4 63.6 75.7 63.4 62.7 63.9 67.2 75.4 82.1 104.2 82.7 88.5 65.6 56.4 regression equation: Enter the equation in slope-intercept form with parameters accurate to three decimal places.
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 2.5 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) 7.6 7.4 9.8 8.8 9.3 7.3 Weight (kg) 142 163 256 188 231 156 The regression equation is y= + x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 2.5 cm is kg? (Round to one decimal place as needed.) Can the prediction be correct? What is wrong with predicting the weight in this case? A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data. B. The prediction cannot be correct because a negative weight does not make sense and because there is…
The personnel director of a large hospital is interested in determining the relationship (if any) between an employee's age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 2 3 4 5 6 7 8 Age 30 50 40 55 30 28 60 25 Sick Days 7 4 3 2 9 10 0 8 Copy Data The estimated regression line and the standard error are given. Sick Days = 14.310162 - 0.2369(Age 9 10 30 45 5 2 Se = 1.682207 Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places.

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