linear correction coefficient given to determine the coefficient of determinatio
ID: 3158761 • Letter: L
Question
linear correction coefficient given to determine the coefficient of determination. R^2. r = 0.38 R^2 = 61.64% R2 = 14.44% R^2 = 6.16% R^2 = 1.444% an appropriate response. A manufacturer of boiler drums wants to use regression to predict the number of man-hours needed to erect drums in the future. The manufacturer collected a random sample of 35 boilers and measured the following two variables: MANHRS: y = Number of man-hours required to erect the drum PRESSURE: x_1= Boiler design pressure (pounds per square inch, i.e, psi) Initially, the simple linear model E(y) = beta_0 + beta_1x_1 was fit to the data. A printout for the analysis appears below: UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF MANHRS R-SQUARED 0.4342 RESID. MEAN SQUARE (MSE) 4.25460 ADJUSTED R-SQUARED 0.4176 STANDARD DEVIATION 2.06267 Give a practical interpretation of the coefficient of determination, R_2 Express R_2 to the nearest whole percent. ycirc = 1.88 + 0.00321x will be correct 43% of the time. About 43% of the sample variation in number of man-hours can be explained by the simple linear model Man hours needed to erect drums will be associated with boiler design pressure 43% of the time. About 2.06% of the sample variation in number of man-hours can be explained by the simple linear model.Explanation / Answer
B is the answer.
Rsq = 0.4342
Hence 43% of variation of dependent variable is explained by variation in independent variable
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