Previously, I transformed categorical data into numeric format for analytical purposes. During this process, I pondered whether there might be a connection between age and armed status. Consequently, I conducted a correlation analysis specifically focusing on the armed statuses: armed with a knife, armed with a gun, and unarmed, as they exhibit high occurrence in the dataset. The obtained correlation coefficients are as follows:
- Armed with a Knife: -0.011807: This value is very close to zero, indicating an extremely weak or negligible correlation between age and the likelihood of being armed with a knife. The negative sign suggests a slight negative correlation, but its magnitude is minimal.
- Armed with a Gun: 0.088604: This positive value points to a weak positive correlation between age and the likelihood of being armed with a gun. However, the correlation is relatively modest, implying that age and being armed with a gun are not strongly linearly associated.
- Unarmed: -0.128284: This negative value suggests a weak negative correlation between age and the likelihood of being unarmed. Although the correlation is still relatively small.
These values only capture linear relationships. Other factors and nonlinear relationships may also play a role in understanding the data.