Run a regression analysis on the following bivariate set of data with y as the response variable.y22.750.225.45624.257.710.834.626.854.526.160.418.443.725.555.430.457.735.477.827.458.617.746Find 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 asa percentage accurate to one decimal place. (If the answer is 0.84471, then it would be 84.5%..you wouldenter 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 29.5 as theexplanatory 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 =

In this case, x is the independent variable, and y is the dependent variable.

Answered: Run a regression analysis on 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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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
The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, Y=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in dollars 31 38 42 44 46 Number of Bids 3 4 6 7 9 Summation Table X Y XY X2 Y2 BID 1 31 3 93 961 9 BID 2 38 4 152 1444 16 BID 3 42 6 252 1764 36 BID 4 44 7 308 1936 49 BID 5 46 9 414 2116 81 SUM 201 29 1219 8221 191 Step 1: Find the estimated slope. Step 2: Find the estimated y-intercept. Step 3: Determine the value of the dependent variable Y at x=0. Step 4: Find the estimate value of y when x=42. Step 5: Substitute the values you found in steps 1 and 2 into the equation for the…
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 =
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 =…
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
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.)
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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 9.15 8.14 8.74 8.77 9.25 8.11 6.12 3.09 9.14 7.26 4.74 Click here to view a table of critical values for the correlation coefficient. Ay 10- Ay 10- 本Y 10- y 10- 8- 8- 6- 8- 8- 6- 6- 6- 4- 4- 4 4. 2- 2- 2- 2- 0- 4 8 12 16 4 8 12 16 4 18 12 16 4 8. 12 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r= (Round to three decimal places as needed.)
Here is a bivariate data set. X y 69 73.4 69.1 64.9 67.9 69.3 81.3 65.1 66.1 71.1 65.5 70.3 51.9 85.9 35 70.8 53.2 66.6 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. R2 =

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