So, assuming that W 0 is the intercept and W 1 is the coefficient in a simple linear regression model, the way to calculate a t statistic for W 1 is( W 1 − 0 ) /std error of W 1 how do I calculate the t statistic for W 0 ?

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So, assuming that       W          0       is the intercept and       W          1       is the coefficient in a simple linear regression model, the way to calculate a t statistic for       W          1       is(      W          1      −      0      ) /std error of       W          1      how do I calculate the t statistic for       W          0      ?

saniraore · Accepted Answer

Test statistic for any individual regression coefficient (this determined whether a specific regressor makes a contribution to the model).Null Hypothesis:       H          0        :      β          j        =  0 where   j is the   j-th term in the model (intercept or another term).Alternative Hypothesis:       H          A        :      β          j        ≠  0 (significance)Test Statistic:       t          o      b      s        =                              β          ^                            j                    s      e      (                                    β            ^                                    j                    )        ,  d  f  =  n  −  k  −  1All of these   t-statistics appear in the Analysis of Variance table.

So, assuming that W0 is the intercept and W1 is the coefficient in a simple linear regression model, the way to calculate a t statistic for W1 is (W1-0) /std error of w1 How do I calculate the t statistic for W0?

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