PREFACE

Our goal in writing this book was to generate an accessible and relatively complete introduction for undergraduates to the use of statistics in the biological sciences. The text is signed for a one quarter or one semester class in introductory statistics for the life sciences. The target audience is sophomore and junior biology, environmental studies, biochemistry, and health sciences majors. Appropriate prerequisites include some coursework in biology as well as a foundation in algebra but into calculus, Examples are taken from many areas in the life sciences including genetics physiology, ecology, agriculture, and medicine.

This text emphasizes the relation ships between probability, probability distributions, and hypothesis testing. We have tried to highlight the expected value of various text statistics under the null and research hypotheses as a way to understand the methodology of hypothesis testing. In addition, we have incorporated nonparametric alternatives to many situations along with the standard parametric analysis. These nonparametric techniques are included because undergraduate student projects often involve sampling populations where the underlying distribution is unknown, and because the development of the nonparametric tests is usually readily understandable for students with modest math backgrounds. The nonparametric can be skipped or skimmed without any loss of continuity.

We have tried to include interesting and easily understandable examples with each concept. The problems at the end of each chapter have a range of difficulty and come from variety of disciplines. Most are not real life examples but are realistic in their design and data values. The end of chapter problems are randomized within each chapter to require the student to choose the appropriate analysis. Many undergraduate texts present a concept or text and immediately give all the problems that can be solved by that technique. This approach prevents students from having to make the real life decision about the appropriate analysis. We believe this decision making is a critical skill in the introduction of statistical analysis and have provided a large number of opportunities to practice and develop this skill.

The material for this text derives principally from a required biostatistics  course one has taught to undergraduates for more than 20 years and from a second course in nonparametric statistics and field data analysis that the other of us has taught more recently during several term abroad programs to Queensland , Australia. Recent shifts in undergraduate curricula have deemphasized calculus for biology students and are now highlighting statistical analysis as a fundamental quantitative skill. Hopefully our text will make teaching and I learning what skill somewhat less arduous.