Skewed Distributions in Data Science.

Generally, data points cluster on one side more than the other. We call these types of distributions __________.

In Left Skewed Distribution data points cluster on the _____side of the distribution, then the tail would be longer on the ______side.

In Left Skewed Distribution the tail is longer in the _______ Direction and the Mode _______ Median _______ Mean.

In Right Skewed Distribution data points cluster on the _____side of the distribution, then the tail would be longer on the ______side.

In Right Skewed Distribution the tail is longer in the _______Direction and the Mode ___ Median___ Mean.

A Density plot is a smoothed, _______ version of a histogram estimated from the data.

Kernel density estimation (KDE) is a ________ curve (the kernel) is drawn at every individual data point and all of these curves are then added together to make a single smooth density estimation.

If Quantiles are cut points dividing the range of a probability distribution into continuous intervals with equal probabilities or dividing the observations in a sample in the same way.

Then Answer the following.

2 quantile is known as the__________
4 quantile is known as the __________
10 quantile is known as the__________
100 quantile is known as the _________

The Q-Q plot or quantile-quantile plot is a _______plot created by plotting two sets of quantiles against one another.

Skewness is also another measure to check for normality which tells us the amount and direction of the skewed data points. Generally for the value of Skewness:

If the value is less than -0.5, we consider the distribution to be _________skewed where data points cluster on the right side and the tails are longer on the left side of the distribution

Whereas if the value is greater than 0.5, we consider the distribution to ____________skewed where data points cluster on the left side and the tails are longer on the right side of the distribution

And finally, if the value is between -0.5 and 0.5, we consider the distribution to be approximately __________.

Another numerical measure to check for Normality is Kurtosis.
Kurtosis gives the information regarding tailedness which basically indicates the data distribution along the ________.

For the symmetric type of distribution, the Kurtosis value will be close to_______. We call such types of distributions as Mesokurtic distribution. Its tails are similar to Gaussian Distribution (Normal).

In cases, where the value of K is greater than zero. Tail will be ______ and will have ________distribution. We call such types of distributions as Leptokurtic Distribution.

In cases, where the value of "K" is less than zero. Tail will be ______ and will have ________distribution. We call such types of distributions as Platykurtic Distribution.