Consider the following.XyX332.11125.96432.421223.88532.941324.3632.461424.22730.981522.148Determine the correlation coefficient to three decimal places of accuracy.27.81622.96926.721721.481028.7418yUse the set of data to calculate the regression line using a calculator or other technology tool. (Round the coefficients to three decimal places.)y =19.3

Answered: Image /qna-images/answer/3b536a86-b74e-4077-a87b-c3997cbddd22.jpg

Answered: X y X 3 32.1 11 4 32.42 12 5 32.94 13 6…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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1
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation?
Run a regression analysis on the following bivariate set of data with y as the response variable. x y 61.1 78.9 58.6 84.5 70.2 58.1 62.3 65.4 64.2 68.9 58 84.1 63.7 70.2 64.6 71.9 68.3 71.5 61.7 77.5 59.3 77.4 64.6 71.2 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 61.9 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? (Report answer accurate to one decimal place.)
Here is a bivariate data set. Find the regression equation for the response variable y. X y 32.6 50.4 56.5 9.4 74.6 8.8 42.6 86.6 73.8 -16.6 66.4 29.6 53.9 28.5 40.7 93.7 33.2 88.1 65.9 5.2 52.9 46.9 regression equation: Enter the equation in slope-intercept form with parameters accurate to three decimal places.
How do find the answer on paper and the TI84
Run a regression analysis on the following bivariate set of data with y as the response variable. x y 52.4 51.4 54.9 58.3 47.7 10.3 51.2 33.6 70.7 94 37.9 1.2 42.2 38.6 72.8 71.9 74.1 108.3 44.6 20.3 51.8 54.3 47.7 52.5 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 57.8 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 =
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 = %
5. Explain what the correlation coefficient tells you about the relationship between your variables. 7. Interpret the slope of the regression equation in terms of the variables in your data set.
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.)
Next Run a regression analysis on the following bivariate set of data with y as the response variable. X y 48.1 41 63.7 62.6 40.1 33.4 49.4 46.3 16.3 -29.1 39.9 27.3 37.1 33.3 48.2 45.4 32.9 11.1 34.9 27.9 44.6 25.5 25.1 Z 23.2 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 = % Submit Question
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 44 inches. Is the result close to the actual weight of 293 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 45 221 265 50 41 52 45 335 307 45 265 Critical Values of the Pearson Correlation Coefficient r 321 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? Critical Values of the Pearson Correlation Coefficient r a = 0.05 a = 0.01 0.990 NOTE: To test Ho: p=0 y=+x (Round to one decimal place as needed.) 4 against H,: p#0, reject H, jf the absolute value of r is greater than the critical value in the table. 0.950 0.878 0.959 6 0.811 0.917 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 0.684 0.661 13 0.553 14 0.532 15 0.514 0.641 0.497 16 17 18 19 0.623…
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