<?xml version="1.0" encoding="utf-8"?><!DOCTYPE article  PUBLIC '-//OASIS//DTD DocBook XML V4.4//EN'  'http://www.docbook.org/xml/4.4/docbookx.dtd'><article><articleinfo><title>FAQ/lnuse</title><revhistory><revision><revnumber>2</revnumber><date>2016-07-28 08:55:20</date><authorinitials>PeterWatson</authorinitials></revision><revision><revnumber>1</revnumber><date>2016-07-28 08:55:08</date><authorinitials>PeterWatson</authorinitials></revision></revhistory></articleinfo><section><title>Use of natural logs in data transformations</title><para>(The below is taken from <ulink url="http://stats.stackexchange.com/questions/27682/what-is-the-reason-why-we-use-natural-logarithm-ln-rather-than-log-to-base-10"/>): </para><para>In the context of linear regression in the social sciences, Gelman and Hill write[1]: </para><para>We prefer natural logs (that is, logarithms base e 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. </para><para><emphasis role="underline">Reference</emphasis> </para><para>[1] Andrew Gelman and Jennifer Hill (2007). Data Analysis using Regression and Multilevel/Hierarchical Models. Cambridge University Press: Cambridge; New York, pp. 60-61. </para></section></article>