This book will discuss basic statistical analysis methods through a series of biological
examples using R and R-Commander as computational tools. The book is
intended for a wide range of readers, from people with relatively strong analytical
background who want to learn about statistics and its application in biology, to
nonstatistician scientists who use statistical methods in their research.
While the theoretical aspects of statistics are intriguing and interesting on their
own, we believe that what separates statistics from other branches of mathematics is
its intimate relationship with other fields, such as biology, economics, and social sciences,
and its widespread application in these areas. In statistics, a theoretical work
is usually inspired by applied problems, and new theories usually find immediate
applications in real-world problems. This interweaving of theory and application
has put statistics in a special place in the scientific world.
In this book, most topics are motivated by real examples first. We believe that
learning a new topic becomes easier if it is motivated by interesting and engaging
applied problems. We also hope that this approach helps students to improve their
critical thinking and problem-solving skills for situations where they are presented
with new problems. To this end, we motivate each new topic with a relevant problem
from biology. We then try to reach the solution intuitively before discussing the
related statistical methods. For example, when discussing Bayes’ theorem, we first
present a biological problem (finding the probability of lung cancer for smokers)
and find the answer to that problem intuitively based on what we already know.
Then, we introduce Bayes’ theorem as a general form of our solution for this type
of problem.
While discussing statistical methods and their applications, our goal is to keep
a balance between mathematical rigor and readability. To accomplish this, we have
moved concepts that tend to be more complex with limited applications in everyday
analysis to the end of each chapter in “Advanced” sections. For the most part, these
sections could be skipped in the first reading of this book.
Throughout the book, we use R-Commander, a free and publicly available computer
program, to show how statistical methods can be used in practice. We believe
that using these methods while learning them could help with the learning process.