A thorough understanding of biology, no matter which subfield, requires a thorough understanding of statistics. As in previous editions, Havel and Hampton (with new co-author Scott Meiners) ground students in all essential methods of descriptive and inferential statistics, using examples from different biological sciences. The authors have retained the readable, accessible writing style popular with both students and instructors. Pedagogical improvements new to this edition include concept checks in all chapters to assist students in active learning and code samples showing how to solve many of the book's examples using R. Each chapter features numerous practice and homework exercises, with larger data sets available for download at waveland.com.
Limnology, stream ecology, and wetland ecology all share an interdisciplinary perspective of inland aquatic habitats. Scientists working in these fields explore the roles of geographic position, physical and chemical properties, and the other biota on the different kinds of plants and animals living in freshwaters. How do these creatures interact with each other and with their physical environment? In what ways have humans impacted aquatic habitats? By what methods do freshwater ecologists study these environments? With this new laboratory manual, Havel provides a variety of accessible hands-on exercises to illuminate key concepts in freshwater ecology. These exercises include a mixture of field trips, indoor laboratory exercises, and experiments, with some portions involving qualitative observations and others more quantitative. With the help of this manual, students will develop an appreciation for careful techniques used in the laboratory and in the field, as well as an understanding of how to collect accurate field notes, keep a well-organized lab notebook, and write clear scientific reports.
A thorough understanding of biology, no matter which subfield, requires a thorough understanding of statistics. As in previous editions, Havel and Hampton (with new co-author Scott Meiners) ground students in all essential methods of descriptive and inferential statistics, using examples from different biological sciences. The authors have retained the readable, accessible writing style popular with both students and instructors. Pedagogical improvements new to this edition include concept checks in all chapters to assist students in active learning and code samples showing how to solve many of the book's examples using R. Each chapter features numerous practice and homework exercises, with larger data sets available for download at waveland.com.
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