Steve Figard - Introduction to Biostatistics with JMP

This book is based on the need for a college-level textbook with examples derived from the biological sciences as an introduction to biostatistics using JMP software. The contents of this book follow that of an introductory course on biostatistics created for and taught at Bob Jones University and reflects an intended audience of undergraduates forced to take a course they really rather wished they could avoid. These undergraduates generally have enough biological and mathematical knowledge to be dangerous, coupled with an innate fear of Statistics, that renders them quite dangerous indeed. Although a basic knowledge of math up to and including algebra is generally desirable, this work studiously avoids the underlying formulas and mathematical gyrations found in many of the more comprehensive books on statistics. This is by design. Most practitioners of statistics are not mathematicians, dont care about the underlying math, and are content to let their software deal with those details as long as they can get the answers that they need with some assurance that they are correct. To that end, the emphasis here will be on how to set up and execute the statistical tests in JMP and how to interpret the output.

Before getting into the details of the individual tests, however, it is necessary to cover some basics of how to think like a statistician, or a reasonable facsimile thereof, to ensure that the right analysis is being done in the first place. The reader will find most of these preliminaries in the first chapters, with their application to specific tests being covered in the remaining chapters. The ultimate goal is to create bioscientists who can competently incorporate biostatistics into their investigative toolkits to solve biological research questions as they arise.

Given the intended audience of this work undergraduate biology and health science majors the question asked in this section title is probably best answered by the opening paragraph of Dawn Hawkins excellent book when she writes:

Let us consider the likely scenario that you are a student of the biosciences. Whether you are a biomedic, a physiologist, a behaviourist, an ecologist, or whatever, you like learning about living things you enjoy learning about the human body, bugs, and plants. Now, lo and behold, you have been forced to take a course that will make you do things with numbers and, dread-o-dread, even do something with numbers using a computer. You have probably decided that the people who are making you do this are mindless sadists.

This captures many of the expressions I see on the first day of class on all too many of my students. Lest this seems to be an exaggeration, I have been asking those students to write down a one-word description of how they feel about taking this course and collecting those

responses. Using the text explorer feature in JMP to create a word cloud, I have acquired the following words to date:

Note that the majority of students are nervous, unsure, afraid or anxious as opposed to excited or intrigued. (Although it is intriguing that so many use that word to describe a biostatistics course at all!)

But I will argue here that we are neither mindless nor sadists in our demand that you, as a promising practitioner of the biological sciences, learn how to do statistics.

There are at least three reasons why this is so. First, if you are going to be a scientist of any kind, you should have some understanding of the philosophy and history of science. This is the big picture into which you will orient your own efforts at contributing to the body of knowledge. The twentieth century saw a paradigm shift in the basic philosophy underlying the scientific enterprise. The prior century, in part due to successful efforts in astronomy at understanding the movement of planets and other heavenly bodies, had developed a philosophical determinism in which mathematic formulas led to precise predictions. As David Salsburg notes,

Science entered the nineteenth century with a firm philosophical vision that has been called the clockwork universe. It was believed that there were a small number of mathematical formulas (like Newtons laws of motion and Boyles laws for gases) that could be used to describe reality and to predict future events. All that was needed for such prediction was a complete set of these formulas and a group of associated measurements that were taken with sufficient precision.