Week 2 – Wednesday

Kurtosis

From what I understand, Kurtosis is a statistical measure that helps us understand the shape of a probability distribution, or the “peak” and “tail” of a data set. When we plot a graph for the data, it forms a bell shape curve.

Types of Kurtosis

1. Mesokurtic : Kurtosis = 3.0

A mesokurtic distribution is one where the kurtosis is close to zero.

2. Leptokurtic : Kurtosis > 3.0

A leptokurtic distribution has positive kurtosis.

3. Platykurtic : Kurtosis < 3.0

A platykurtic distribution has negative kurtosis.

If a data set has a high kurtosis, that means the distribution has a very sharp peak and heavy tails. In practice, this refers to the data having more extreme values, either exceptionally high or exceptionally low, compared to a normal distribution.

On the opposite side, low kurtosis indicates a smoother, broader distribution with light tails. In this case, the data have fewer extreme values ​​and are more concentrated around the mean.

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