this is an hour tutorial got two minutes learn some statistical programming in our it's easy free and fun this tutorial how to generate a Bernoulli or binomial distribution without quaking in fear in our this tutorial builds on the random number generation tutorial how to generate random numbers according to different statistical distributions in our so be sure to try that one on for size if things aren't clear in this video we're going to avoid the heavier statistical concepts here but I'll just say a Bernoulli distribution is an abstract way to think about an event that either happens or it doesn't for example a coin flip has two outcomes heads or not heads which would be tails but it's easier to think about it as heads or not heads or say seeing a man dressed in a gorilla costume on your drive to work has two possible outcomes either you see the gorilla Kai or you don't for a coin flip the probability is 50/50 that it's heads you don't see a guy dressed in a gorilla costume on most days on your drive to work so let's say the probability of seeing a guy dressed in a gorilla costume on your drive to work is one out of a thousand okay great alright let's generate some random numbers with our use the our binome the our biome function has three parameters the number of random numbers to generate the number of trials that occur in each random number you generate and the probability that an event will occur what's all that mean if you're trying to create create a Bernoulli distribution then the size parameter will always be one period end of story so here's what the function does our randomly flips a coin ten times and it looks like four of those ten times are came up with heads and the other six time it came up with not heads which is tails hey let's make it quote unquote flip a coin a hundred thousand times and it looks like well about half of the coin flips our heads and half and the coin flips are not heads neat alright let's test out the probability of seeing a guy in a gorilla costume when you drive to work remember we decided that the probability was about one out of a thousand that you would see the guy in the gorilla costume when your drive to work if you drive to work ten times or you never saw the guy in the gorilla costume but let's say you drive to work ten thousand times you might have a sighting right let's save that result into X and now X contains a couple of sightings there's a sighting there's a sighting there's a sighting up there if we take the sum of all the sightings it looks like out of ten thousand times you had a gorilla guy costume sighting ten 13-time this has been a work of our