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2020-11-04
hey everyone this is unearthed from Adi Rekha in this session let me walk you through how Python can be used for statistics and probability well guys this session is intended to be useful for anyone who is considering to kick-start their learning about pipes in statistics or probability and you need some insight about the language well the focus sure is to basically approach the framework in the easiest way possible so let's begin by checking out the agenda for the session we will start with the introduction to statistics and probability and later we'll start with how we need Python for probability and we look at the view of the concepts lastly will end this session with an exciting use case that I'm sure all of us can make use of so let's begin by checking out why we need pie thin for statistics well we're all familiar with our R as a language dedicated for statistics right so if that's the case then why would we require Python for statistics again well it's not just statistics right we're gonna mix data sticks with image analysis or text mining or any other complex pipeline as well to do that Python really helps us and the richness of Python is definitely an invaluable asset here and that would make our life so much easier right well if you were to ask my opinion if I had to start out with statistics again I think I would definitely start out with Python and then probably consider R well that's this person preference so moving on let's check out what probability actually means well at the most basic level probability seeks to answer the question what is the chance of an event happening right we look at it this way and event is some outcome out of interest to calculate the chance of an event happening we need to also consider all the other events that can occur at that point of time as well right well to elaborate more on this let's consider the coin toss problem right it's a classic problem for this purpose well there are two events you are and these are considered to be the sample space well what do we mean by sample space it's basically all the outcomes for the coin toss so when you toss a coin there are only two chances and two occurrences right so it's basically either you get a heads or you get a tail and if it's a fair coin I don't think there can be any other possibility as well so it's just heads or its tails so basically these two form the samples in our case the set of all the possible events that can happen right so that's about it to calculate the probability of an event occurring we would have to count how many times the event of interest can occur say how many times you flip the coin and it landed on heads or how many times you flip the coin and it landed on tails right and eventually we divide this total number by the sample space so in our case the sample space is only two because we only have a one in two chance right so it is either has to be heads or it has to be tails well the probability will tell us that our ideal...
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