Skewness

Description

Skewness is a statistical measure of the symmetry of a distribution. Use to understand the distribution of data, such as the price data of a cryptocurrency.

A distribution is said to be symmetrical if it has a bell-shaped curve, with the majority of the data points clustered around the middle and tapering off towards the ends. A distribution is said to be skewed if it is not symmetrical, with the data points tending to be more concentrated on one side.

Two types of skewness: positive skewness and negative skewness.

Positive skewness occurs when the data points are more concentrated on the left side of the distribution, with a longer tail on the right side. This indicates that there are more lower values and a few higher values.

Negative skewness occurs when the data points are more concentrated on the right side of the distribution, with a longer tail on the left side. This indicates that there are more higher values and a few lower values.

Skewness is used to describe the shape of the price distribution and provides insight into the market trends. If the price distribution is positively skewed, it indicates that the price is more likely to move upwards. If the price distribution is negatively skewed, it indicates that the price is more likely to move downwards.

Use skewness in combination with our other tools to make informed decisions.

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