I have always been fascinated by statistics. In my opinion, It is one of those subjects that is useful regardless of what your domain is. It is not on

Coding for Statistics: Develop an Intuition for Statistics Using Programming

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2021-07-22 12:00:08

I have always been fascinated by statistics. In my opinion, It is one of those subjects that is useful regardless of what your domain is. It is not only helpful as a tool to understand the world better but also captivating in its own right. Subjects like Bayesian Theorem can really go against our intuitive tendencies and reveal the shortcomings in our thinking.

If you don't know what Bayesian Theorem is, you should read up about it. In short, it tells us that the possibility of occurrence of an event is primarily dictated by the prevalence of that event in the general population. It sounds like an obvious statement when it is put that way, but we have a strong tendency to overlook this.

Say you are exhibiting some inexplicable medical symptoms, and search the internet to understand what that might mean. The internet lets you know, in a typical fashion, that some form of rare cancer might explain your symptoms. Now your inclination might be to believe that you might indeed have a high chance of having that disease since there is an overlap in symptoms. But, controlling for everything else, the probability of you having that problem is still incredibly low even though you have some of those symptoms. Remember that this is a rare disease. You still need to be very unlucky to actually have it. You having those symptoms at the moment doesn't increase the probability as much as your imagination might lead you to think, assuming those symptoms can have other, more common, explanations. This is not to say you shouldn't seek medical advice, but you can actually keep a cool head till you get an explanation and not stress over something you have read on the internet.

The Monty Hall Problem, a problem inspired by a popular game show in the 60s, is a statistical puzzle that can be equally confusing.

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