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Biomeasurement: A Student's Guide to Biological Statistics by Dawn Hawkins (Paperback, 2019)

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Yet, despite being a collection of the most valuable and important tools available to bioscientists, statistics is often the aspect of study most feared by students. It goes on to presentthe key statistical tests, walking the student step-wise through the use of each, with carefully-integrated examples and plentiful opportunities for hands-on practice.

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A refreshing, student-focused introduction to the use of statistics in the study of the biosciences. Emphasising why statistical techniques are essential tools for bioscientists, Biomeasurement removes the stigma attached to statistics by giving students the confidence to use key techniques for themselves.Key Features:Includes the best online resources and software support for bioscience students needing to integrate statistics into their studies and apply it in their researchExplains why statistics are needed, how to choose and carry out statistical analyses, and how their results can be interpreted.Focuses on the application of statistics as a valuable research tool, avoiding detailed treatment of the mathematical basis of statisticsEmphasises explanations so that students are guided through the key concepts and techniques in a steady, progressive wayEnables students to build confidence in handling actual data through the use of real datasetsIllustrates the use of the techniques in published research work through 'Literature Links', which highlight the importance of statistics in real-world science and demonstrate how to report results in a professional mannerComes with a strong suite of accompanying online resources for students and teachers including helpsheets and screencasts for using SPSS and R, as well as datasets, and interactive calculation sheets.New to This Edition:New sections giving guidance on sample size choices and their consequencesAn additional 'Choosing Chart' for graphs to help explore and communicate dataA new checklist for reporting results in tables and figuresFuller treatment of frequency data and their handling in chi-square tests using SPSSExpanded online support for R and SPSS, including additional example datasets.