With this Dashboard, the above two graphs show the changes in time for the chosen two variables, the target years can be determined by the user as well. The graph below indicates the scatter plot for each chosen group, the group level also can be changed, and it will be applied other graphs accordingly. Moreover, there is also a cluster world map to group countries regarding their values into four clusters.

As an example, High-technology export(% manufactured export) (HT) and Research and Development expenditure (% GDP) (RD) are chosen to analyze them and their relations for each group level. Income level is an important factor to differentiate for those selected values, as it is seen in the tables above. Moreover, the relationships between two variables change also for a given grouping level. For instance, the relationship between RD and HT is positive and significant for low, upper-middle, and high-income countries, it is negative for lower-middle-income countries although it is not significant. As cluster world map shows that many countries are clustered as Cluster 1 as small RD and HT, and countries, like Germany and the USA, are categorized as Cluster 3 high RD and HT, and countries, like China and Mexico, are counted in Cluster 2 as small RD and high HT, and Cluster 4 has just Philippines as outlier.