A simple linear regression model was used to describe the relationship between y = hardness of molded plastic and x = amount of time elapsed since the end of the molding process. Summary quantities included n = 16, SSResid = 1235.470, and SSTo = 25,221.368. (a) Calculate an estimate of ?. (Round your answer to three decimal places.) What value for degrees of freedom is associated with this estimate? (b) What percentage of observed variation in hardness can be explained by the linear relationship between hardness and elapsed time? (Round your answer to one decimal place.)
A simple linear regression model was used to describe the relationship between y = hardness of molded plastic and x = amount of time elapsed since the end of the molding process. Summary quantities included n = 16, SSResid = 1235.470, and SSTo = 25,221.368. (a) Calculate an estimate of ?. (Round your answer to three decimal places.) What value for degrees of freedom is associated with this estimate? (b) What percentage of observed variation in hardness can be explained by the linear relationship between hardness and elapsed time? (Round your answer to one decimal place.)
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A simple linear regression model was used to describe the relationship between y = hardness of molded plastic and x = amount of time elapsed since the end of the molding process. Summary quantities included
n = 16,
SSResid = 1235.470,
and
SSTo = 25,221.368.
(a)
Calculate an estimate of ?. (Round your answer to three decimal places.)
What value for degrees of freedom is associated with this estimate?
(b)
What percentage of observed variation in hardness can be explained by the linear relationship between hardness and elapsed time? (Round your answer to one decimal place.)
_____%
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