Mathematical equations are only useful when you can apply them to solve a social problem or, in other words, serve society through computing. We do this through the convergence of multiple interdisciplinary fields.
Before you try to computationally solve a problem, always consider breaking it down into a series of categorized steps:
- Problem outline: Finding the nature of the problem and choosing the most effective way of solving it and displaying the result
- Problem solution: Choosing the most effective mathematical formula to solve the problem
- Program code: Programming the underlying solution to the problem
- Solution testing: Applying the previous methodologies to solve a computational problem with Python code to provide an effectively programmed solution
For example, tobacco is linked to many diseases, including cancer. To understand this better, we can try to correlate tobacco consumers to different cases of those diseases. So, our first dataset (array) in that case would be the tobacco consumer population in different regions. Our second dataset would be disease cases in the same respective regions.