Introduction 1

Introduction

B

iostatistics is the practical application of statistical concepts and techniques

to topics in the biology and life sciences fields. Because these are broad

fields, biostatistics covers a very wide area. It is used when studying many

types of experimental units, from viruses to trees to fleas to mice to people.

Biostatistics involves designing research studies, safely conducting human

research, collecting and verifying research data, summarizing and displaying the

data, and analyzing the data to answer research hypotheses and draw meaningful

conclusions.

It is not possible to cover all the subspecialties of biostatistics in one book, because

such a book would have to include chapters on molecular biology, genetics,

agricultural studies, animal research (both inside and outside the lab), clinical

trials, and epidemiological research. So instead, we focus on the most widely

applicable topics of biostatistics and on the topics that are most relevant to human

research based on a survey of graduate-level biostatistics curricula from major

universities.

About This Book

We wrote this book to be used as a reference. Our intention was for you to pull out

this book when you want information about a particular topic. This means you

don’t have to read it from beginning to end to find it useful. In fact, you can jump

directly to any part that interests you. We hope you’ll be inclined to look through

the book from time to time, open it to a page at random, read a page or two, and

get a useful reminder or pick up a new fact.

Only in a few places does this book provide detailed steps about how to perform a

particular statistical calculation by hand. Instruction like that may have been

­necessary in the mid-1900s. Back then, statistics students spent hours in a com-

puting lab, which is a room that had an adding machine. Thankfully, we now have

statistical software to do this for us (see Chapter 4 for advice on choosing ­statistical

software). When describing statistical tests, our focus is always on the concepts

behind the method, how to prepare your data for analysis, and how to interpret

the results. We keep mathematical formulas and derivations to a minimum. We