[Ebook PDF] Statistics for the Life Sciences, 5th Edition

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[Ebook PDF] Statistics for the Life Sciences, 5th Edition

ISBN-13: 978-0321989581
ISBN-10: 9780321989581

Author: Myra Samuels (Author), Jeffrey Witmer (Author), Andrew Schaffner (Author)

The Fifth Edition of Statistics for the Life Sciences uses authentic examples and exercises from a wide variety of life science domains to give statistical concepts personal relevance, enabling students to connect concepts with situations they will encounter outside the classroom. The emphasis on understanding ideas rather than memorizing formulas makes the text ideal for students studying a variety of scientific fields: animal science, agronomy, biology, forestry, health, medicine, nutrition, pharmacy, physical education, zoology and more. In the fifth edition, randomization tests have been moved to the fore to motivate the inference procedures introduced in the text. There are no prerequisites for the text except elementary algebra.

PREFACE
Statistics for the Life Sciences is an introductory text in statistics, specifically addressed to students specializing in the life sciences. Its primary aims are (1) to show students how statistical reasoning is used in biological, medical, and agricultural research;
(2) to enable students to confidently carry out simple statistical analyses and to interpret the results; and (3) to raise students’ awareness of basic statistical issues such as randomization, confounding, and the role of independent replication.
Style and Approach
The style of Statistics for the Life Sciences is informal and uses only minimal mathematical notation. There are no prerequisites except elementary algebra; anyone who can read a biology or chemistry textbook can read this text. It is suitable for use by graduate or undergraduate students in biology, agronomy, medical and health sciences, nutrition, pharmacy, animal science, physical education, forestry, and other
life sciences.
Use of Real Data Real examples are more interesting and often more enlightening than artificial ones. Statistics for the Life Sciences includes hundreds of examples and exercises that use real data, representing a wide variety of research in the life sciences. Each example has been chosen to illustrate a particular statistical issue. The exercises have been designed to reduce computational effort and focus students’ attention on concepts and interpretations.
Emphasis on Ideas The text emphasizes statistical ideas rather than computations or mathematical formulations. Probability theory is included only to support statistical concepts. The text stresses interpretation throughout the discussion of descriptive and inferential statistics. By means of salient examples, we show why it is important that an analysis be appropriate for the research question to be answered, for the
statistical design of the study, and for the nature of the underlying distributions. We help the student avoid the common blunder of confusing statistical nonsignificance with practical insignificance and encourage the student to use confidence intervals to assess the magnitude of an effect. The student is led to recognize the impact on real research of design concepts such as random sampling, randomization, efficiency,
and the control of extraneous variation by blocking or adjustment. Numerous exercises amplify and reinforce the student’s grasp of these ideas.
The Role of Technology The analysis of research data is usually carried out with the aid of a computer. Computer-generated graphs are shown at several places in the text. However, in studying statistics it is desirable for the student to gain experience working directly with data, using paper and pencil and a hand-held calculator, as well as a computer. This experience will help the student appreciate the nature and purpose of the statistical computations. The student is thus prepared to make intelligent use of the computer—to give it appropriate instructions and properly interpret the output. Accordingly, most of the exercises in this text are intended for hand calculation. However, electronic data files are provided
Organization
This text is organized to permit coverage in one semester of the maximum number of important statistical ideas, including power, multiple inference, and the basic principles of design. By including or excluding optional sections, the instructor can also use the text for a one-quarter course or a two-quarter course. It is suitable for a terminal course or for the first course of a sequence.
The following is a brief outline of the text.
Unit I: Data and Distributions
Chapter 1: Introduction. The nature and impact of variability in biological data. The hazards of observational studies, in contrast with experiments. Random sampling.
Chapter 2: Description of distributions. Frequency distributions, descriptive statistics, the concept of population versus sample.
Chapters 3, 4, and 5: Theoretical preparation. Probability, binomial and normal distributions, sampling distributions.
Unit II: Inference for Means
Chapter 6: Confidence intervals for a single mean and for a difference in means.
Chapter 7: Hypothesis testing, with emphasis on the t test. The randomization test, the Wilcoxon-Mann-Whitney test.
Chapter 8: Inference for paired samples. Confidence interval, t test, sign test, and Wilcoxon signed-rank test.
Unit III: Inference for Categorical Data
Chapter 9: Inference for a single proportion. Confidence intervals and the chisquare goodness-of-fit test.
Chapter 10: Relationships in categorical data. Conditional probability, contingency
tables. Optional sections cover Fisher’s exact test, McNemar’s test, and odds ratios.
Unit IV: Modeling Relationships
Chapter 11: Analysis of variance. One-way layout, multiple comparison procedures, one-way blocked ANOVA, two-way ANOVA. Contrasts and multiple comparisons are included in optional sections.
Chapter 12: Correlation and regression. Descriptive and inferential aspects of correlation and simple linear regression and the relationship between them.
Chapter 13: A summary of inference methods.