F-test statistic for the slope

Consider the simple linear regression model $y_i = \alpha + \beta x_i + \epsilon_i, \; i = 1, 2, \dots, 24$, where $\alpha \in \mathbb{R}$ and $\beta \in \mathbb{R}$ are unknown parameters, the errors $\epsilon_i$'s are i.i.d. random variables having $N(0, \sigma^2)$ distribution, where $\sigma > 0$ is unknown. Suppose the following summary statistics are obtained from a data set of 24 observations $(x_1, y_1), \dots, (x_{24}, y_{24})$: $S_{xx} = \sum_{i=1}^{24} (x_i - \bar{x})^2 = 22.82$, $S_{yy} = \sum_{i=1}^{24} (y_i - \bar{y})^2 = 43.62$, and $S_{xy} = \sum_{i=1}^{24} (x_i - \bar{x})(y_i - \bar{y}) = 15.48$, where $\bar{x} = \frac{1}{24} \sum_{i=1}^{24} x_i$ and $\bar{y} = \frac{1}{24} \sum_{i=1}^{24} y_i$. Then, for testing $H_0: \beta = 0$ against $H_1: \beta \ne 0$, the value of the $F$-test statistic based on the least squares estimator of $\beta$, whose distribution is $F_{1,22}$, equals (rounded off to two decimal places)