In Simple Linear Regression, Most Often We Perform a Two-Tail $$\beta _ { 1 }$$

In simple linear regression, most often we perform a two-tail test of the population slope $$\beta _ { 1 }$$ to determine whether there is sufficient evidence to infer that a linear relationship exists. Which of the following best describes the null and alternative hypotheses needed for a test of significance? $\begin{array}{|l|l|}\hline A&H_{0}: \beta_{0}=0 \\&\mathrm{H}_{\mathrm{a}}: \beta_{0} \neq 0\\\hline B&\mathrm{H}_{0}: \beta_{1} \neq 0\\&\mathrm{H}_{a}: \beta_{1}=0 \\\hline C&\mathrm{H}_{0}: \beta_{0}=0 \\&\mathrm{H}_{\mathrm{a}}: \beta_{0} \neq 0\\\hline D&\mathrm{Ho}: \beta_{1}=0\\&\mathrm{H}_{a}: \beta_{1} \neq 0 \\\hline \end{array}$