Circumference and Age Narrative
Evidence supports using a simple linear regression model to estimate the circumference of a pine tree based on its age. Let x be the age of the pine tree (measured in years) and y be the circumference (measured in cm). A random sample of 11 mature pine trees was selected and the following data recorded: The following output was generated using statistical software: Regression Analysis
The regression equation is
y = -148 + 4.18x S = 4.025 R-Sq = 96.4% R-Sq(adj) = 96.0%
Analysis of Variance Table Unusual Observations R denotes an observation with a large standardized residual
-Six points have these coordinates: The normal probability plot and the residuals versus fitted values plots generated by statistical software are shown below. Does it appear that any regression assumptions have been violated? Explain.

Question

Circumference and Age Narrative
Evidence supports using a simple linear regression model to estimate the circumference of a pine tree based on its age. Let x be the age of the pine tree (measured in years) and y be the circumference (measured in cm). A random sample of 11 mature pine trees was selected and the following data recorded:  The following output was generated using statistical software:  Regression Analysis
The regression equation is
y = -148 + 4.18x  S = 4.025 R-Sq = 96.4% R-Sq(adj) = 96.0%
Analysis of Variance Table  Unusual Observations  R denotes an observation with a large standardized residual
-Six points have these coordinates:  The normal probability plot and the residuals versus fitted values plots generated by statistical software are shown below. Does it appear that any regression assumptions have been violated? Explain.

Quizplus · Accepted Answer

The Answer of Circumference and Age Narrative
Evidence supports using a simple linear regression model to estimate the circumference of a pine tree based on its age. Let x be the age of the pine tree (measured in years) and y be the circumference (measured in cm). A random sample of 11 mature pine trees was selected and the following data recorded:  The following output was generated using statistical software:  Regression Analysis
The regression equation is
y = -148 + 4.18x  S = 4.025 R-Sq = 96.4% R-Sq(adj) = 96.0%
Analysis of Variance Table  Unusual Observations  R denotes an observation with a large standardized residual
-Six points have these coordinates:  The normal probability plot and the residuals versus fitted values plots generated by statistical software are shown below. Does it appear that any regression assumptions have been violated? Explain.