What does "Log-normal Distribution" mean?
Table of Contents
The log-normal distribution is a way to describe how certain values, like sizes or prices, are spread out. It happens when a variable's logarithm follows a normal distribution, which means that when you take the log of the values, they fit a bell-shaped curve.
Characteristics
Positivity: All values in a log-normal distribution are positive. This makes it useful for measuring things that can't be negative, like income or the size of particles.
Skewed Shape: Unlike a normal distribution, which is symmetric, a log-normal distribution has a long tail on one side. This means that most values cluster around a smaller number, but there can be some very high values.
Multiplicative Effects: It often represents situations where a value is the result of many small factors multiplying together. For example, the price of a stock can be influenced by many small changes in the market.
Applications
Log-normal distributions are common in finance, biology, and other fields. They can help model things like income distribution among a population or the sizes of particles in a sample. By understanding this distribution, we can get insights into how certain processes work in the real world.