Statistics-Left Skewed And Right Skewed Distribution And Relation With Mean, Median And Mode

hello all my name is krishnak and welcome to my youtube channel so guys morning ad actually asked you a statistical question which was recently asked in an interview to one of my subscriber as you all know guys most of the interview questions whichever i get to know i am definitely uploading that in my interview playlist and whenever i find out any new questions i'll probably make a video with respect to that so let me just tell you what was the question basically asked and for that in the morning also i had actually created a video many of you actually gave the right answer and yes many of you were also actually confused okay with respect to the question that i had asked so the question was that just tell us some of the classical examples of the right skew distribution and the left skid distribution and the second question was that what is the relationship between the mean median mode of right skill distribution and the left skill distribution now first of all we'll try to understand what exactly is right skew distribution and left skill distribution now guys whatever data you take and probably if you're trying to plot it in the form of histogram in the form of kernel density estimator and whenever you see this kind of right hand side elongated line right like this like this kind of distribution this is basically called as right skewed data okay that basically means your right side right hand side of this particular curve is little bit elongated when compared to the left hand side right now some of the classical examples over here so i'm just going to take some of the example the first example that i would like to take is wealth distribution this is a very classical example which recruiters also like to hear just imagine some of the top most richest people like elon musk jeff from amazon mark zuckerberg bill gates they usually fall in this particular region even ambani and they are very less number of people you know who follows in this specific reason whereas in this particular region you will be finding people with the same amount of wealth right this is one classical example the second classical example that i would like to take is probably you can you know that like you have seen my channel you have seen most of my videos guys you'll be seeing that some of the people like to write a longer comments right probably after seeing a video so length of the comments length of comments probably in my video this is also a classical example right so here you'll be seeing that some of the people will be writing longer comments they are also some of the people who will be writing smaller comments and some of the people will most of the people will be writing medium size comment probably one liner right so this is two classical examples that i want to give yes in the morning video many people gave some amazing examples itself right and you should also check out that again the link will be given in description now coming to the second uh distribution second distribution which is called a symmetrical distribution this is nothing but our normal distribution this is the example normal distribution i think we have worked out normal distribution with respect to our machine learning problem statement i'll get some of the algorithms once all of the features falling in this kind of most of the features falling in this kind of distribution itself some of the classical example is that age distribution probably weight distribution uh probably height distribution they all follow this kind of normal distribution and even if you have worked with iris data set you saw that in the iris data set you had features like petal length petalwidth sepal length and weight right that was also following this kind of normal distribution and remember guys most of the machine learning algorithm likes the data to have this kind of normal distribution property or and why it is called a symmetrical distribution because the right hand curve will almost be equal to the left hand curve okay so these are like mirror phase fine coming to the third kind of distribution which is also called as left cube distribution it is also called as negative skew distribution here the left hand side will be little bit elongated and then the right hand side right so here the perfect example i'll say lifespan of human being lifespan of human being because there are many people if i talk about the average lifespan it is somewhere around 50 to 70 so 50 to 70 will basically be falling in this particular region there will be people who will be dying quite early in the age but they will be also very less number of people who will be living more than 70 years probably near 100 and all again a perfect example to make you understand yes if you have some more examples definitely many people had also written in the morning and i i like most of the examples itself right now coming to the second question what is the exact relationship with respect to mean median and mode it is very very much simple just by seeing this particular diagram i think you will be able to know it guys mean in the right skewed distribution over here will be greater than median and median will be greater than mode right so mean will be greater than median and median will be greater than mode so this is the exact relationship that you will be able to find just by seeing this particular diagram will be able to understand in the case of symmetrical distribution mean will be approximately equal to median it will be approximately equal to mode so this is the second relationship that you find out with respect to normal distribution the third one basically what you see over here if i take this particular example over here your mode is highest then your median then your mean right so this is the exact relationship let me just write it down if you are getting confused first the highest will be mode then your median you have because median will be obviously smaller than mode then you have mean so this is the relationship that you find out with respect to the negative skewed data so this is what the interviewer may be expecting probably remember whenever this kind of questions are asked always make sure that you know some of the examples because if you tend to forget this particular topics also just with the help of those examples will be able to explain it in a proper way trust me guys practical knowledge definitely understanding of that theoretical is very very much important if you are able to relate this theoretical thing with some practical stuff you will be able to understand you will be able to relate once you able to relate it you will be able to understand you will be able to explain it okay so this is what i really wanted to cover just let me know whether you like this kind of thing or not because every day i'll at least come up with one interview questions probably and then i'll try to explain you completely from end to end so i hope you like this particular video please do subscribe the channel if you're not already subscribed i'll see you in the next video have a great day ahead thank you and all bye

Channel: Krish Naik

Views: 34,556

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Id: 0djtjjy12fI

Length: 6min 51sec (411 seconds)

Published: Thu Apr 08 2021