<P> If β ^ ( \ displaystyle \ scriptstyle ( \ hat ( \ beta ) ) ) is an ordinary least squares estimator in the classical linear regression model ( that is , with normally distributed and homoscedastic error terms ) , and if the true value of parameter β is equal to β , then the sampling distribution of the t - statistic is the Student 's t - distribution with ( n − k ) degrees of freedom , where n is the number of observations , and k is the number of regressors ( including the intercept ) . </P>
<P> If β ^ ( \ displaystyle \ scriptstyle ( \ hat ( \ beta ) ) ) is an ordinary least squares estimator in the classical linear regression model ( that is , with normally distributed and homoscedastic error terms ) , and if the true value of parameter β is equal to β , then the sampling distribution of the t - statistic is the Student 's t - distribution with ( n − k ) degrees of freedom , where n is the number of observations , and k is the number of regressors ( including the intercept ) . </P>
how many degrees of freedom does the ​ t-statistic have
how many degrees of freedom does the ​ t-statistic have
n − k ) degrees of freedom , where n is the number of observations , and k is the number of regressors ( including the intercept ) .
n − k ) degrees of freedom , where n is the number of observations , and k is the number of regressors ( including the intercept ) .