## Introduction

We have seen that the easiest distribution pattern to analyze is
unimodal and symmetric. Sometimes we can make a data distribution
more nearly unimodal and symmetric if we change the units of the
measurements: that is, transform the measurements. The result is to
make the analysis and interpretation of the data distribution pattern
easier. Two examples are the measure of acidity known as pH (the
negative logarithm of the concentration of hydrogen ions in a
solution) and the measure of earthquake magnitudes known as the
Richter scale (the logarithm of the energy released by the
earthquake).

## Objectives

In this lab, you will be introduced to the family or power transformations,
which are often used to transform data to a form more suitable for analysis.
You will see how different transformations change the pattern of variation
in a set of data. To learn about power transformations, click on the button
to the left.