There are three kinds of lies: lies, damned lies, and statistics.

- Mark Twain

Statistics are like a bikini. What they reveal is suggestive, but what they conceal is vital.

- Aaron Levenstein

Researchers, especially academic and scientific journals, are fascinating, not just in terms of the researches, but in how selective the topics, hypotheses and tiny and skewed sample sizes are. And all this are often enhanced through “statistical analysis” using various theories - your pearson, spearman, kurtosis, regression, parametric etc.

The more you understand the concept and root of these theories, the more you’ll realize how whacked the idea of “assumptions based on assumptions” are made substantial. This perhaps defies that the mother of failures are assumptions - or maybe it doesn’t because we've become a headline society, ignoring the fine prints hidden in these journals.

Similarly, mathematical tools such as ratios, algebra, and matrices, while powerful, harbor their own set of assumptions. What appears as a "favorable unit" may not authentically represent the underlying dynamics of flow or value.

But by then, the excitement catches creating a wave of crowd hype. Over time, what was once a hot topic fades into habit and culture. Even if many months later, the true nature of findings are revealed, it no longer matters. Madness of crowd has picked up and will carry on. This madness has existed for centuries.

If we were to look back and ask ourselves - how often do we dig into something to a point of really understanding it, not just the operations but its applications and impact on the world ?

How often do we believe it blindly because it’s a hype or because our friends and respected figures whom we deem to be smart have already looked through and gave their raving reviews? How often do we not want to be seen “stupid” for asking what might be seen as the “basic” questions ? How easily are we influenced?