# What is asymmetric distribution?

An skewed distribution refers to a probability distribution that is uneven and skewed in nature. Unlike a standard normal distribution, which resembles a bell-shaped curve, skewed distributions are shifted to one side, having a longer tail on one side relative to the other side of the median. The other side of the curve will have a peak of clustered values ​​where the most data points occur. This type of distribution curve is generally classified as having a positive or negative slope, depending on the direction of displacement of the curve.

In general, an skewed distribution is said to have a positive slope if the tail of the curve is longer on the right side compared to the left side. This skewed distribution is also known as right skew because the right side has a wider spread of data points. Positive slope curves have the most values ​​for the left side of the curve.

In contrast, negatively skewed distributions have most data points on the right side of the curve. These curves have longer tails on the left sides, so they are said to be slanted to the left. An important rule of thumb for determining the direction of bias is to consider the length of the tail rather than the location of the mean or median. This is because asymmetry is ultimately caused by the farthest values, which extend the curve to that side of the graph.

Understanding the properties of an skewed distribution is important in many statistical applications. Many people assume that the data follows a bell curve, or normal distribution, so they also assume that a graph has zero bias. However, these assumptions can lead them to misinterpret information about the actual distribution.

A skewed distribution is inherently skewed in nature, so it will not follow standard normal patterns such as standard deviation. Normal distributions imply a standard deviation that applies to both sides of the curve, but skewed distributions will have different standard deviation values ​​for each side of the curve. This is because the two sides are not mirror images of each other, so equations that describe one side cannot be applied to the other. The standard deviation value is generally larger for the side with the longer tail because there is more data spread out on that side compared to the shorter tail.

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