In the previous part of this block, we made some designs that could be useful to understand the correlations and trends between variables. Understanding the relationships between variables brings us more closer to extracting some important informations which brings more clearity to what the data expresses. Subsequently, policy decisions are made base on this important informations.
The first figure above shows the relation between suicide numbers and sex through out the years from every country. Figure two goes further to help us better understand the retaionship between suicide number and sex within each generation, again through out the years. We observe that at a very large margin, males turn to comit more suicide than females and this in all generations. With the larger and smaller margin from the boomer generation and generation Z respectively.
It is important to observe the suicide rate through out the years. We notice a bump in the years 1999 and 2000, and a flattening curve till 2016.
In the subsequent publications, it will be interesting for us to study the spike in suicide numbers in the years 1999 and 2000 in all geneartions except for the G.I generation. What was happening in the years earlier that stopped to cause this sudden increse and why was the G.I generation not affected.