Question

When testing linear restrictions, the test statistic is assumed to follow the $y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \epsilon$, you wish to test $H_0: \beta_1 = \beta_2 = 0$ versus $H_A$: Not all sopes are 0. The value of the test statistic is $F(1,30) = 7.75$ and its associated $p$-value is 0.0092. At the 1% significance level, the conclusion is to not reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is significant not reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is not significant reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is not significant reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is significant

          When testing linear restrictions, the test statistic is assumed to follow the $y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \epsilon$, you wish to test $H_0: \beta_1 = \beta_2 = 0$ versus $H_A$: Not all sopes are 0. The value of the test statistic is $F(1,30) = 7.75$ and its associated $p$-value is 0.0092. At the 1% significance level, the conclusion is to
not reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is significant
not reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is not significant
reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is not significant
reject the null hypothesis and conclude that the influence of $x_1$ and $x_2$ on $y$ is significant

When testing linear restrictions, the test statistic is assumed to follow the y = β0 + β1x1 + β2x2 + ϵ, you wish to test H0: β1 = β2 = 0 versus HA: Not all sopes are 0. The value of the test statistic is F(1,30) = 7.75 and its associated p-value is 0.0092. At the 1% significance level, the conclusion is to
not reject the null hypothesis and conclude that the influence of x1 and x2 on y is significant
not reject the null hypothesis and conclude that the influence of x1 and x2 on y is not significant
reject the null hypothesis and conclude that the influence of x1 and x2 on y is not significant
reject the null hypothesis and conclude that the influence of x1 and x2 on y is significant

Added by Nicole M.

Question

Please give Ace some feedback