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# This job sums t-statistic and includes a discussion of hypothesis testing.

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"The output of an estimated regression equation shows the t-statistic for a given coefficient associated with an independent variable to be 1.99."

Explain the implications of this statement in the context of ordinary least squares regression? Be sure your answer includes a discussion of hypothesis testing.

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The solution explains the implications of this statement in the context of ordinary least squares regression.

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For linear regression model: Yt=β0+β1X1 +......+βkXk,t+Ut
Xt is a set of independent variables; Yt is the dependent variable. βt are unknown population coefficients; Ut is a disturbance term which captures the error between X and Y.
The estimation of the model is: Yt=b0+b1X1,t +......+bkXk,t +et
Bk is the sample estimate of βk; et is the residual.
Here Bk is estimated by minimizing the sum of squared errors, and referred to as ...

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