But you can also see why this is tricky. What do I mean when I say you cross the room blindfold 1 billion times? You’re aging during this experiment and would be dead before the experiment was completed. This is a stupid example, you can’t really do this. If you only do it a million times, then you’re not going to be able to get a good estimate of the probability. Is it .999999 or 1.0? How about crossing the freeway? Well you’ll probably die within the first 10 times of trying. So how can you do this 100 times? It’s also a stupid example.

So you can try to get around this by saying that you have 100 parallel and identical universes where you stand on the side of the freeway, ready to cross blindfolded, all for the cause of science. But this won’t work because if they’re all identical, you’ll get the same result for each one of them (forgeting about quantum mechanics). So you’ll decide that you either cross safely with probability 1 or probability 0.

That’s why they say that the concept of probability is tricky. Well that’s one reason people like to talk about rolling dice or tossing coins. You can repeatedly toss a coin over and over again and expect that the outcome of one toss won’t effect another. You’d also think that if you do a coin toss today, the likelihood of it coming up heads would be the same as in two weeks from now. Then you can ask questions like: ”What’s the probability that the coin will land heads?” Or ”what’s the probability the coin will land tails two times in a row”?”

But the coin tossing experiment isn’t actually as good an example of probability as you’d think. The coin doesn’t really land in a random way at all. So you might be tempted to say: ”this stuff about probability sucks, I’m not into tossing coins or Jackass anyway”. But I’m not saying it’s useless, it’s incredibly useful, but stuff in the real world is always like this. There are always pitfalls to any modeling of real data, and probability is no worse than others. In fact it’d be far worse not to attempt to model probabilistic effects in real world situations. The whole subject of statistics is based on probability. So probability has applications in all of the sciences, including physics, chemistry, biology, medicine sociology and psychology. It’s also incredibly important to engineering, economics, financial markets, and marketing. But because it’s pretty subtle, it’s misapplied all the time. That’s why is important to understand it and not just apply some stupid formula for a standard deviation which can result in the completely wrong conclusion i.e. crossing the freeway blindfold.