The eternal number game
Data is eternal but at the same time, it’s also deceptive. We can zero in on certain cohorts to ascertain our hypothesis and yet, we’ll never really manage to scratch the back of truth. This is the case mainly because of our innate clash of perspectives. If you randomly gather 50 people and ask them a set of questions that appeal to their emotional well-being, your ultimate understanding would become a factor of how they felt that particular day.
For example, if the questionnaire was designed to gauge the happiness index, your result will be different on different days although the same cohort is being questioned. The reason is quite simple: we remain the same but we tend to experience different days. Someday, we are cheerful and some days, we turn antsy. Someday, we are motivated and on others, we are punctured flat. Our environment is seldom tunable so, left without any choice, we end up tuning ourselves according to the environment. In other words, happiness index is a byproduct of sadness in one’s immediate existence. It’s difficult to maintain a happy face when your head is splitting and the Saridon isn’t working as it’s supposed to.
We can pretty much disown any type of date piece out there as easily as we can own anything related to data. Why? Because getting absolutes is out of question. There are way too many people. There are way too many emotions. There are way too many excuses. Time is precious and everybody’s getting bored. So, what we try to do with what we’ve got at our disposal is we hope to look at the trends. If 6 out of 10 people in a group prefer pizza over dosa, the remaining 4 are left without any agency to represent them or their taste in dosa. That’s data science. It’s a number game. And like all disciplines associated with math, there is no end to it.
The bullshit will continue as long as there is an audience.
To give you an example, nobody cares to know how many of us are interested in having those red payphones back in our lives. Given India’s rural realities, we might be surprised to know that quite a lot of people, especially those above a certain age bracket, must be missing a useful chunk of technology they heavily relied on in the outdoor. There is no data available for such heuristics. Data, or should we say, the guardians of data, cater to the popular streams. We often read about the farce behind calling India a vegetarian country, especially when the majority of the citizens have meat as an essential constituent of their diet. However, none of the data geniuses would pluck us the percentage of those who consume meat on a daily basis. If there are pure vegetarians, shouldn’t there be something called pure non-vegetarians too? Of course, we can’t compete with the carnivorous Mongols of the 13th century but still. It’s one thing to consume meat on a weekly basis and quite another to have it every single day. Because a so-called non-veggie could very well be a person who consumes 6 days of vegetarian diet and one blissful Sunday lunch of kori rotti. In such a scenario, there is no match between “vegetarian” person and a “non-vegetarian” person. The sanctity of data is missing.
As mentioned earlier, data is trustworthy only as long as it serves a purpose. Which is why I conducted an arbitrary 3 month-long study of my own. During my daily commutes, I either use bike taxi or the good ol’ autorickshaw and I make it a point to ask the riders/drivers a very straightforward question: In your everyday job, who do you come across more — nicer folks or ruder folks? I’ve posed this query to 114 men so far and all of them had the same answer: nicer passengers always outnumber the ruder ones.
Being a thoroughbred cynic, I haven’t given up on my study yet and still waiting for a negative reply.
