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Consider the Following Partial Computer Output for a Multiple Regression

question 210

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Consider the following partial computer output for a multiple regression model.
 Predictor  Coefficient (bi)  Standard Dev (sb)  Constant 99.3883X10.0072070.0031X20.00113360.00122X30.93240.373 Analysis of Variance SS Source  df 31.308 Regression 39.378 Error (residual)  16\begin{array} { l l l } \text { Predictor } & \text { Coefficient } \left( \mathrm { b } _ { \mathrm { i } } \right) & \text { Standard Dev } \left( \mathrm { s } _ { \mathrm { b } } \right) \\\text { Constant } & 99.3883 & \\\mathrm { X } 1 & - 0.007207 & 0.0031 \\\mathrm { X } 2 & 0.0011336 & 0.00122 \\\mathrm { X } 3 & 0.9324 & 0.373 \\& & \\\text { Analysis of Variance } & & \mathrm { SS } \\\text { Source } & \underline { \text { df } } & 31.308 \\\text { Regression } & 3 & 9.378 \\\text { Error (residual) } & 16 &\end{array}
-What is the mean square error?


Definitions:

N = 20

Denotes a sample size of 20 in statistical terms, referring to the number of subjects or units in a study or experiment.

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