simple linear regressio

The desired linear model is 14 10 2008 raj jain

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The desired linear model is:
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14-10 ©2008 Raj Jain CSE567M Washington University in St. Louis Example 14.1 (Cont) Example 14.1 (Cont)
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14-11 ©2008 Raj Jain CSE567M Washington University in St. Louis Example 14. (Cont) Example 14. (Cont) ! Error Computation
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14-12 ©2008 Raj Jain CSE567M Washington University in St. Louis Derivation of Regression Parameters Derivation of Regression Parameters ! The error in the ith observation is: ! For a sample of n observations, the mean error is: ! Setting mean error to zero, we obtain: ! Substituting b0 in the error expression, we get:
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14-13 ©2008 Raj Jain CSE567M Washington University in St. Louis Derivation of Regression Parameters (Cont) Derivation of Regression Parameters (Cont) ! The sum of squared errors SSE is:
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14-14 ©2008 Raj Jain CSE567M Washington University in St. Louis Derivation (Cont) Derivation (Cont) ! Differentiating this equation with respect to b 1 and equating the result to zero: ! That is,
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