Last week, we looked at how quantum physics can teach us a thing or two about problem solving in small data environments. Some of the most path breaking work in Physics started with a theory, refined by mathematical models and then proved (or disproved) with experiments. This week, let’s take a look at Biology –... Continue Reading →

# Problem Solving: Learning from other disciplines

Richard Feynman Richard Feynman (he doesn’t need an introduction) was a consummate problem solver. When asked about his problem-solving techniques, his colleague Murray Gell-Mann (a Nobel Laureate himself) defined the ‘Feynman Problem Solving Algorithm’: Write down the problemThink very hardWrite down the answer While this was partly in jest, this to me captures why it... Continue Reading →

# Solving hard problems

Over the last few posts, I had explored the overall idea of how to approach the problem of decision making in a world of ‘tail events’ and insufficient data. And increasingly, it is clear that most Analytics teams in organizations are not very well equipped to navigate this order of complexity. Over the next couple... Continue Reading →

# Bayes meets Markov: Let the chain reaction begin …

I started this mini-series with the need to create models that could work with tail events, working with small data and inferential thinking. In our final installment (and probably the densest!), I want to dip our toes into the world of simulations to help us navigate the business problem landscape in this ‘new normal’. As... Continue Reading →

# Bayes: What is the big deal?

It would be no understatement to say that Thomas Bayes was an obscure figure in the much-storied annals of mathematics and logic for a better part of the last 100 years. And then something happening in the last 10 years and now, he is everywhere – and has even entered mainstream culture by the eponymous... Continue Reading →

# Data Science: is Statistical modeling enough?

Hat tip: the great Bill Watterson We are all in online forums with endless discussions about everything related to the current coronavirus situation. My college (IIT Delhi) group is no exception – what is far more interesting is that every once in a while, we go down analysis rabbit holes on a variety of topics:... Continue Reading →

# Navigating extreme events with small data

Here’s a thought experiment: Fred and Bay want to run a coin toss experiment. They want to make sure that the coin is completely unbiased – so they go to the US Mint and get a quarter that has passed all its tests (i.e. there is no manufacturing defect[1]); toss the coin 100 times. They... Continue Reading →

# Of Tail Events

Thales of Miletus was a Greek mathematician and a pre-Socratic philosopher, generally regarded as the first philosopher on the Greek tradition. And here’s an interesting story about him: he predicted the weather and a good olive harvest for a particular year. He went a step further and reserved all the olive presses in advance at... Continue Reading →

# Is the new normal ‘non-normal’?

When all of this is over, we will look back and think about why we ended up at a point where these stark, difficult choices had to be made - and what can we do to avoid these extreme situations in future? Needless to say, decision making under these conditions is hard - but then... Continue Reading →