Given a linear model

$$

y = beta_0 + beta_1x_1 + beta_2x_2+beta_3x_3 + beta_4x_4

$$

we can perform an $F$-test for the null hypothesis

$$

H_0: beta_1 = beta_2 = beta_3 = beta_4 = 0

$$

However, what test is appropriate for a subset of these coefficients being zero in the same model?

$$

H_0': beta_1 = beta_4 = 0

$$

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#### Best Answer

You can use still an F-test. The test statistic is: $$F_0 = dfrac{SS_R/2}{MS_E},$$ where $SS_R$ is the increasing in the residual sum of squares of the reduced model (setting $beta_1=beta_4=0)$ with respect the full model with all the parameters. $MS_E$ is the residual sum of squares of the full model divided by $n-5$, where $n$ is the number of the observations.

Under $H_0$, $F_0$ is distributed as a $F_0$ of Fisher-Snedecor with $d_1=2$ (i.e. number of restrictions) and $d_2=n-5$.

**Remark:** clearly the result is valid under the usual assumptions of the Linear regression (e.g. Gaussian residuals).

See here the details of what they call *partial* *F* *Test*.

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