With the Dashboard, the tables above show scatter plots for the chosen country. Whereas the table at the link indicates for row values, the right one demonstrates for calculated values. In order to make a detailed analysis, there are two calculation options. Since some values like growth rate vary a lot over the years, moving average, which is calculating a four-year average, may be used. Furthermore, some variables, like human capital, are cumulative. Percentage differences can be therefore a valid option to avoid misanalysis. Besides, it may be sometimes needed that some variables should be used as they are, so that there is also an option without applying any calculation. Additionally, there is a cluster world map to determined which group the country belongs to. The range of years for the map can be also specified by the users.

As an example, the GDP per capita growth and the human capital are chosen to analyze their relationships for South Korea. Regarding the row values analysis, the relationship between variables for Korea is negative and significant. However, after calculating a moving average for GDP per capita growth and percentage differences for human capital, the direction of the relationship changed, and it became positive and significant. In terms of clusters, Korea belongs to Cluster 1 by taking into account the average values of countries from 1960 to 2017 given values.