How long will we live? A Practical Approach to linear regression
Recently I found myself in the situation of explaining in a simple way what linear regression was and what it was for.
Once explained I was told: “it only works with linear data, it will never be needed”.
In part, this statement may also be true, but the world does not always “fluctuate” or evolve exponentially and twisted in everyday life.
An example? Life expectancy!
In these few passages, I wanted to share a simple practical case in which it is worth using linear regression, the prediction of life expectancy.
If we look at the data we can immediately see that life expectancy in the united states from 1860 to 2020 has grown following a fairly linear trend.
Now we can implement our amazing linear regression using the sklearn library.
Now we can safely know that:
2025 -> 85.57
2030 -> 87.07
Conclusions and Personal thoughts
As we can see, we could say with some approximation that life expectancy has doubled in the last 100 years or so, following a fairly linear trend.
But if we observe the technological evolution, especially linked to information technologies, we notice instead of an exponential trend.
This leads me to ask what happened? why does the evolution in the field of “life” not follow the technological evolution?
At the moment I don’t know how to answer these questions, but surely this difference in trend implies the need to further enhance research in the medical field relating to people’s health and life.
Will we be able to convert this trend? Will our children be able to live 200, 300, 1000 years? (I am currently 21 years old)
Only technology, time and thousands of people who work in the field of life can tell us, for the moment I just observe.
May the Data be with you.
Made with love by Antonio Scapellato