Log-normal distribution

What Log-normal distribution is

Log-normal distribution is a type of continuous probability distribution which is often used to model a random variable that is the product of many independent processes. It is also referred to as the Galton distribution or the Gibrat distribution.

Steps for Log-normal Distribution:

  1. Calculate the mean and variance of the data.
  2. Transform the data into its logarithmic form.
  3. Fit the logarithmic data to a normal distribution.
  4. Calculate the parameters for the log-normal distribution.
  5. Plot the log-normal distribution.
  6. Estimate the probability of a given value.

Examples

  1. Log-normal distributions are commonly used to model financial returns, such as stock prices, earnings, or dividends.

  2. Log-normal distributions are often used in reliability engineering, to model the distribution of system lifetimes.

  3. Log-normal distributions are also used to model the size distribution of certain natural phenomena, such as particles, grains, and even trees.

  4. Log-normal distributions are also used in epidemiology to model the distribution of certain diseases in a population.

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