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for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory;
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A Hands-On Approach to Teaching Introductory Statistics Expanded with over 100 more pages, Introduction to Statistical Data Analysis for;
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This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical;
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A concise introduction to data analysis for beginners and intermediate students using IBM - Statistical Package for Social Sciences (SPSS);
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introduction to thebioinformatics science for statistical and computational studentsand audiences who have not experienced such analysis tasksbefore.;
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Data Analysis and Presentation Skills: An Introduction for the Life and Medical Sciences is an invaluable text allowing students to;
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Data Analysis and Presentation Skills: An Introduction for the Life and Medical Sciences is an invaluable text allowing students to;
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Experimental Design and Statistical Analysis for Pharmacology and the Biomedical Sciences A practical guide to the use of basic principles;
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This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The;
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This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The;
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Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a;
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Provides an excellent introductory text for students on the principles and methods of statistical analysis in the life sciences, helping;
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in biomedical data analysis.This book gives a new and integrated introduction to quantitative medical data analysis from the viewpoint;
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Now in its second edition, this textbook provides an introduction to Python and its use for statistical data analysis. It covers common;
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featured in data analysis and data science. The author- a noted expert in quantitative teaching -has written a quick go-to reference for performing;
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sciences. This book provides a self-contained introduction to parametric modeling, exploratory analysis and statistical interference for extreme;
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The purpose of this book is to provide an introduction to the concepts of statistical analysis of data for students at the undergraduate;
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approaches to quantitative longitudinal data analysis in the social sciences. The book introduces definitions and terms, explains the relative;
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continues to teach students the basic concepts of data description and statistical inference as well as the statistical methods necessary for real;
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presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the;
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presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the;
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and R contains an accessible introduction to statistical modeling techniques commonly used in the social and natural sciences. The text offers;
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Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between;
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Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between;
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Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand. This;
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Most environmental data involve a large degree of complexity and uncertainty. Environmental Data Analysis is created to provide modern;
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sciences who will benefit from a stronger understanding of how to analyze empirical data. The book is written for those with foundational education;
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