We prefer natural logs (that is, logarithms base e) because, as described above, coefficients on the natural-log scale are directly interpretable as approximate proportional differences: with a coefficient of 0.06, a difference of 1 in x corresponds to an approximate 6% difference in y, and so forth.

What is the purpose of ln?

Given how the natural log is described in math books, there's little “natural” about it: it's defined as the inverse of , a strange enough exponent already. But there's a fresh, intuitive explanation: The natural log gives you the time needed to reach a certain level of growth.

Why is ln used in statistics?

In statistics, the natural log can be used to transform data for the following reasons: To make moderately skewed data more normally distributed or to achieve constant variance. To allow data that fall in a curved pattern to be modeled using a straight line (simple linear regression)