STATISTICS- What are Random Variables and It's Types and its Importance?

[Music] hello all my name is Krishna and welcome to my youtube channel today we are going to basically discuss what are random variables and what are those different types now guys this random variable plays a very important role again in machine learning because every feature you know every feature that is present in your data set is basically a random variable and I guess it can be of different types which I'm going to discuss so in this particular session the agenda you basically be that I'll be discussing what is exactly random variable then the second type is that what are the different types of random variable and then the third technique is that in random variable we basically have two types one is numerical random variable and the other one is something called as this is a categorical random variable right numerical random variable and category random variable now apart from this in this particular session only I'll be also discussing what are the two different kinds of numerical variable numerical random variable so over here I basically have something called as discrete random variable and I have something called as continuous random variable right I'll be also discussing about how what are exactly catechol variables random variables and we'll also be discussing a lot about its types as we go ahead so let us discuss what exactly is random variable now random variable can be any name that you are basically using suppose I'm using X I can basically store something in this particular variable itself okay so this is just like a placeholder when I am storing something okay now you can store anything it may be a string it may be an integer value it may be a sentence it may be anything okay it may also be a category Chur okay now let me just give you some example suppose I want to create a variable where it stores a Jazz's value so I can basically write X is equal to 24 okay so here basically X is a random variable which is storing basically 24 as its value okay similar I can also store some sentence X is equal to hello okay so here I'm basically storing a word in this particular variable okay so random variable is something that stores some value in it so that we can use that particular value wherever you want okay now the next thing is that what are the different types of random variable this is very very important guys because whenever you are working in some data set you should be knowing where the each and every feature what kind of random variables they belong to okay so the first type of random variable is something called as numerical random variable the second type is something called as categorical random variable let me just show you an example of what is a numerical random variable numerical random variable suppose I have feature f1 f2 f3 in my data set suppose my f1 is age now you know that in age I can have numerical values right so I'll be having 23 24 25 27 28 so this is an example of numerical values right now suppose in this the second type is something called as categorical random variable suppose in my future f2 I have something like gender now in gender I can have male female right now here the categorical variable random variable basically indicate that every time this either of this categories will be repeated for each and every record okay so for each and every record you will be seeing that it will be getting continuously repeated that is the property of categorical variable random variable but again I'll be discussing what are the different possibilities of random variable also okay now they are still two types of numerical variable which is numerical random variable one is discrete random variable and one is continuous random variable again let us go and understand discrete random variable so I'll take some examples over here I can see that my discrete random variable can be having something like number of people in the family okay so this is one example discrete random variable basically it indicates that whatever value for this particular variable will be it will be a whole number and it cannot be negative okay it will basically be a whole number and it cannot be negative some of the example number of people in the family right it will be a whole number right you can't say that we are we are having 4.5 people in our house right you'll be saying either we have three people we have four people we have five people now other example may be number of bank accounts that you are having so you will basically say okay I have four banker gonna have five bank accounts again you not say you have four point-five bank accounts right similarly let us take an example of continuous random variable now this continuous random variable basically indicates that you can have any values it can be a floating number it can be decimals number and any any types of values but over here you know in discrete random variable you have a fixed number fixed whole number okay and the number should not be negative some of the examples are salary loan amount interest rate so these are the various examples of continuous random variable okay so here you basically have this many features now why I am explaining you all this particular concepts guys I can remember in my data set I'll be having feature one feature two feature three right feature three may be something your continuous random variable suppose this is my rate of interest okay it may be eight point seven five percent nine point five percent ten percent it may be depending like different different values will be over here so you will be seeing that all our features will at least belong to one of this particular variables and that is why it is important because see in feature engineering which will which I'll be explaining as I go ahead after the statistics playlist you will have to consider various things while you are handling this discrete random variable continuous random variable how to handle this category choose that different different ways to do that so currently we are focusing on statistics but as soon as this gets completed I'll also start feature engineering simultaneously so this was all about this video guys I hope you understood what is random variables and what are is different types this was all about this particular video I'll see all in the next video have a great day please do subscribe the channel if you have not already subscribed till then see you [Music] you

Channel: Krish Naik

Views: 52,734

Keywords: upgrad, Discrete Variables, Categorical Features, greatlearning, coursera, machine learning, Random Variables, appliedaicourse, Continous Variables

Id: uaoj4cN2oYs

Length: 6min 46sec (406 seconds)

Published: Sun Sep 01 2019