Run a regression analysis on the following bivariate set of data with y as the response variable.Xy62.4447.577.259.41672.429.958.1160.784.631.712.5 159.673.540.669.594.767.649.440.2104.434.3136Find 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? Reportanswer as a percentage accurate to one decimal place. (If the answer is 0.84471, then it would be84.5%...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 85.8 asthe explanatory variable. Use a significance level of a = 0.05 to assess the strength of the linearcorrelation.What is the predicted response value? (Report answer accurate to one decimal place.)y =

The bivariate set of data with y as the response variable.

Answered: Run a regression analysis on the…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Based on the data shown below, calculate the regression line and the correlation coefficient. Round each value to three decimal places. y = 14.43 15.86 21.09 4 23.42 22.35 6. 25.08 29.31 8 31.54 9. 31.97 10 36.3 11 39.93 一 N
Here is a bivariate data set. y 54.7 71.7 56 32.8 82.5 79.6 49.7 25.4 73.2 88.1 71.4 78.7 81.1 85.8 39.7 26.5 Find the correlation coefficient and report it accurate to three decimal places. r =
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 =
Here is a bivariate data set. x y 37.7 34.8 35.8 35.4 35.3 38.7 36.7 31.5 44.2 17.6 35.6 35.9 30.6 44 32.6 43.7 35.6 37.2 36 34.7 Use technology to find the correlation coefficient and report it accurate to three decimal places.
Run a regression analysis on the following bivariate set of data with y as the response variable. X y 9.4 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 =
Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.) 10 8 13 9. 11 14 4 12 7 y 7.45 6.77 12.73 7.11 7.81 8.84 6.08 5.39 8.16 6.41 5.72 Click here to view a table of critical values for the correlation coefficient. Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. O A. There is sufficient evidence to support the claim of a nonlinear correlation between the two variables. O B. There is insufficient evidence to support the claim of a nonlinear correlation between the two variables. O C. There is sufficient evidence to support the claim of a linear correlation between the two variables. O D. There is insufficient evidence to support the claim of a linear correlation between the two variables. c. Identify the feature of the data that would be missed if part (b) was completed without constructing…
Run a regression analysis on the following bivariate set of data with y as the response variable. x y 68.5 65.9 88.3 71.6 66.1 61.2 63.6 59.1 67.6 56.7 34.3 47.4 65.4 58.4 59.6 61.1 60.6 54.6 55.2 59.5 67.1 60.7 60.6 57.5 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 81.6 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.)y =…
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Here is a bivariate data set. y 30.4 1.4 28.5 37.7 34.4 46.8 47.9 29.8 23.3 6.3 46.3 32.9 56.6 64.6 42.1 35.1 39.7 41.4 58.5 69.9 Find the correlation coefficient and report it accurate to three decimal places. r =
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.)
Run a regression analysis on the following bivariate set of data with y as the response variable. X 109.4 69.8 90 87.5 64.1 59.6 63.1 92.2 74.7 61.5 83.3 80.3 58.9. 57.3 73 y 61.4 51.6 38.6. 83.7 71.5 69.5 35.4 79.9 40.5 Find the correlation coefficient and report it accurate to three decimal places. r= Based on the data, calculate the regression line (each value to three decimal places) y' = X +
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 = %

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