Skewness And Kurtosis And Moments | What Is Skewness And Kurtosis? | Statistics | Simplilearn

This video, Skewness And Kurtosis And Momentsby Simplilearn, will explain what is skewness and Kurtosis in detail. This lecture on Skewness & Kurtosis And Moments will discuss symmetrical and skewed distribution in Statistics. In addition, you will learn how to calculate Pearson's coefficient of skewness and what kurtosis is.

Here we will discuss the following
00:00 Skewness And Kurtosis And Moments
01:12 Skewed Distribution
03:04 Pearson's Coefficient of Skewness
04:10 Kurtosis

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What is Skewness?
Skewness is used to measure the level of asymmetry in our graph. It is the measure of asymmetry that occurs when our data deviates from the norm.

What is Kurtosis?
Kurtosis is a statistical measure that defines how heavily the tails of a distribution differ from the tails of a normal distribution. In other words, kurtosis identifies whether the tails of a given distribution contain extreme values.

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Got a Question on this topic? Let us know in the comment section below 👇 and we'll have our experts answer it for you. Cheers!

[sannebast]

Could it be that at 2:34 the terms 'mean' and 'mode' should be the other way around in the right graph? Or do I misunderstand?

[peterwestfall]

Kurtosis does not measure the peak at all. The beta(.5, 1) distribution has very low kurtosis but has an infinite peak. Further, the .9999U(0, 1) + .0001Cauchy mixture appears perfectly flat over 99.99% of the observable data, but has infinite kurtosis.

Kurtosis measures tail weight (or more specifically, leverage) only, and nothing about the peak.

[stitaprajnapanda]

In positive skewness the diagram is wrongly labeled

[sakibchowdhury]

The positive skewed diagram is wrong, mode is the biggest in any and every case

[diegoortega]

Pretty much a doozy! Thanks for your explanation dude!

[dollykumari]

Sir u are just reading the content please explain it with easy way....

[ernestjesly]

How to calculate kurtosis. Please Give the formula and some examples .

[germa]

your voice break but good explanation tenks

[Azedjigit]

thank you, could you please make a video in English?