1 - Introduction

Summary

Why do earth scientists need to understand experimental design and statistics?

Earth scientists face special challenges because the things they study – the rock formations, ore bodies, deposits of minerals and fossil species – are often very large, widely dispersed and/or difficult to access. Therefore, it is usually impossible for an earth scientist to study more than a small fraction of any geological phenomenon. For example, imagine trying to measure the length of every brachiopod in the northern hemisphere, the H₂O content of every basalt flow in the USA, the diameter of every volcanic bomb on the island of Hawaii, or the orientation of every single fault plane in an entire formation. You would have to take a sample – a small subset of each – and hope that the results you obtained were representative of the larger group.

Because they are often forced to work with samples, earth scientists need to know how to sample, and they need to know how confident they can be about making generalizations from these samples.

The total number of occurrences of a particular thing (e.g. mineral species, fossil type, rock type) present in a defined area is often called the population. But because a researcher usually cannot measure every part of the population (unless they are studying a very restricted location, like the inside of a volcanic caldera), they have to work with a carefully selected subset of several sampling units that they hope is a representative sample, which can be used to infer the characteristics of the population.