## 4 Discussion
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Country**} & \multicolumn{2}{c}{**Extra-EU**} & \multirow{2}{*}{**Extra-EU**} & \multirow{2}{*}{_ex/gdp_} \\  & **(Values in 1 m \(\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{ }}}}}}}}}}}}}}\))**} & & \\ \hline Austria & 57,579 & 2.34\% & 0.83 \\ Belgium & 181,941 & 7.38\% & 2.10 \\ Bulgaria & 12,195 & 0.49\% & 1.05 \\ Croatia & 6244 & 0.25\% & 0.64 \\ Cyprus & 2560 & 0.10\% & 0.65 \\ Czechia & 44,750 & 1.82\% & 1.09 \\ Denmark & 55,751 & 2.26\% & 0.97 \\ Estonia & 6640 & 0.27\% & 1.25 \\ Finland & 33,122 & 1.34\% & 0.76 \\ France & 252,862 & 10.26\% & 0.59 \\ Germany & 699,363 & 28.38\% & 1.14 \\ Greece & 19,782 & 0.80\% & 0.63 \\ Hungary & 29,295 & 1.19\% & 1.11 \\ Ireland & 117,242 & 4.76\% & 1.63 \\ Italy & 269,906 & 10.95\% & 0.89 \\ Latvia & 7701 & 0.31\% & 1.41 \\ Lithuania & 15,987 & 0.65\% & 1.70 \\ Luxembourg & 3063 & 0.12\% & 0.24 \\ Malta & 1250 & 0.05\% & 0.56 \\ Netherlands & 256,438 & 10.41\% & 1.87 \\ Poland & 86,698 & 3.52\% & 0.88 \\ Portugal & 21,431 & 0.87\% & 0.59 \\ Romania & 21,924 & 0.89\% & 0.53 \\ Slovakia & 20,297 & 0.82\% & 1.22 \\ Slovenia & 16,358 & 0.66\% & 1.84 \\ Spain & 140,367 & 5.70\% & 0.68 \\ Sweden & 83,265 & 3.38\% & 0.92 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: EU external trade statistics (Extra-EU) and derived data. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{1}{c}{**r\({}_{\mathbf{s}}\)**} & \multicolumn{1}{c}{_p_ **(2-Tailed)**} & \multicolumn{1}{c}{**N**} \\ \hline _eu/gdp_ & 0.7658 & 0.00 & 27 \\ _nat/gdp_ & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 9: [PERSON]’s correlation coefficient between the ratios _eu/gdp_ and _nat/gdp_. In order to investigate whether a country's presence in the.eu TLD was measured by the _eu/gdp_ ratio and its presence in EU's national ccTLDs as measured by the _nat/gdp_ ratio, it's _eu/gdp_ ratio [PERSON]'s rho correlation coefficient was calculated for both cases and is presented in Table 11.  
The association between the two variables _eu/gdp_ and _ex/gdp_ can be considered statistically significant by normal standards. This leads to the rejection of the null hypothesis (that there is no correlation between the variables), confirming their positive monotonic relationship. This means that when observing, an increase in the _eu/gdp_ variable will oftentimes be followed by an increase in the _ex/gdp_ variable. The association between the two variables _nat/gdp_ and _ex/gdp_ cannot be considered statistically significant by normal standards, although it is relevantly close to significance. This leads to the acceptance of the null hypothesis, that there is no correlation between the variables. The above measurements, by all means, indicate that each country's use of the.eu TLD is connected to its external trade in a way that is independent from its economy's size as measured by its GDP. In simpler terms, countries that choose to invest and expand in the landscape of the.eu TLD are more likely to have a higher external trade by GDP ratio. They are more likely to have an economy that benefits from exports to countries outside the EU. From an e-commerce perspective, countries that have or are aspiring to have better outreach beyond EU borders are more inclined to present themselves as part of the Union in order to capitalize on the EUs reputation for stability and security. Based on the above consideration, the interrelation between _eu/gdp_ and _ex/gdp_ was again investigated, this time for the 10 EU countries with the lowest external trade revenues in millions of euros. Based on Table 10 these countries are Malta, Cyprus, Luxembourg, Croatia, Estonia, Latvia, Bulgaria, Lithuania, Slovenia, and Greece, all with external trade below 20 billion \(\upmu\). Table 12 presents the results of calculating [PERSON]'s Rho coefficient for these countries.