We have earlier discussed the Normal Distribution, it is also known as the symmetric distribution. But what about the asymmetric distributions. Skewed distributions are the asymmetric distributions. In our previous articles we have seen about Normal Distributions, its applications, and how to calculate or how to solve the problems using different techniques like an empirical rule, Z-Score, Gaussian Mixture Model, etc. We have also seen empirical rule definition, Gaussian Mixture Model definition.
In our today’s article we will discuss the Skewed Distribution, its definition, and sample example how to solve the distribution.
In the normal distribution the graph will show you both sides identical, i.e. both sides will be equal or in other words we can say both sides are symmetric. But it’s somewhat different in the Skewed Distribution. If any of the tails in the graph of the distribution is longer than that of the other the distribution is the skewed distribution. This is also known as the asymmetric distribution or the asymmetrical distribution. We will also see what is the meaning of left-skewed distribution and the right-skewed distribution.
If the left side of the graph has a long tail than that of the right side the distribution is said to be left-skewed distribution. This can be also termed as the negatively skewed distribution. This is because the tail is longer at the negative side of the graph. Also the mean is on the left side of the graph in the distribution.
Whereas it is opposite in the right-skewed distribution. You can see in the graph that the tail is longer in the right-skewed distribution on the right side of the graph, also the mean will be at the right side in the graph.
The normal distribution is a very much common distribution in the studies of statistics. Ahead in statistics you can come across the number of distributions that are negatively skewed.
Mean And Median In The Skewed Distribution
We have seen in the normal distribution the mean and the medians are the same values, but in the skewed distributions you will find that both the values i.e. the mean and the median are different values.
In the above graph of left-skewed distribution you can see that the mean is to the left. And both i.e. the mean and the median are different and with different values.
Whereas, in this graph of right-skewed distribution you can see that the mean is to the right of the graph and the same here also the mean and the median are at the different locations and with the different values.
Effects On Statistics
The normal distribution in the statistical studies is very much easier to learn and to work upon to understand the statistics. But the distributions which we see in real life are always skewed. Much more skewness and the statistical techniques are not of much use. Hence the advanced mathematical techniques which include the logarithms and the quantile regression techniques are used to solve the skewed distribution problems.
Conclusion: hence in this article we have seen about the skewed distribution, and it’s mean and median values, and also what is the effect on the statistical studies.