## Statistical Analysis References

- Online Statistics Education: An Interactive Multimedia Course of StudyThis open and free introductory statistics textbook covers topics typical for a college-level non-math majors statistics course. Topics include distributions, probability, research design, estimation, hypothesis testing, power and effect size, comparison of means, regression, analysis of variance (ANOVA), transformations, chi square, and non-parametric (distribution-free) tests). It is available as a pdf, online, or as an epub. An Instructor's Manual and PowerPoint slides are also available upon request from the project leader at Rice University.
- Introductory StatisticsA free and open introductory statistics textbook for non-math majors. "They have sought to present only the core concepts and use a wide-ranging set of exercises for each concept to drive comprehension. [...] a smaller and less intimidating textbook that trades some extended and unnecessary topics for a better-focused presentation of the central material." It covers descriptive statistics, probability, distributions, discrete and continuous random variables, estimation, hypothesis testing, comparison of means, correlation and regression, chi square, and F-tests.
- Introductory Statistics with Randomization and Simulation"We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods. (1) Statistics is an applied field with a wide range of practical applications. (2) You don't have to be a math guru to learn from interesting, real data. (3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world." This free and open introductory statistics textbook for non-math majors discusses data and data collection, foundations for inference with randomization and simulations (then leading into standard parametric statistics), inference with categorical and numerical data, and linear, multiple logistic regression. An introduction to probability is included as an appendix.

- Statistics for Research byCall Number: QA 276 .D66 2004ISBN: 047126735XPublication Date: 2004"Features the most commonly used statistical techniques for the analysis of research data. [...] emphasis is placed on how to select the proper statistical procedure and how to interpret results."

- Statistics LibreTexts BookshelfCurates multiple openly available statistics textbooks.

- From Numbers to Words byCall Number: HA 29 .M83165 2002ISBN: 080133280XPublication Date: 2001"An invaluable reference tool that guides readers through drafting the results of quantitative experiments." This book gives social science examples but should be of use to learners and researchers in many scientific fields in learning how to report the results of statistical tests.
- Model Selection and Multimodel Inference byISBN: 0387224564Publication Date: 2007"The philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. [...] The text has been written for biologists and statisticians using models for making inferences from empirical data."
- Using Multivariate Statistics byCall Number: QA 278 .T3 2013ISBN: 9780205849574Publication Date: 2012"Provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics." Covers SPSS and SAS code; also available on Reserves at Bizzell Memorial Library.

- Encyclopedia of Statistical Sciences"Reference tool covering statistics, probability theory, biostatistics, quality control, and economics with emphasis in applications of statistical methods in sociology, engineering, computer science, biomedicine, psychology, survey methodology, and other client disciplines." A good source for topics less often covered in the general textbooks.
- The Concise Encyclopedia of Statistics"More than 500 entries include definitions, history, mathematical details, limitations, examples, references, and further readings. All entries include cross-references as well as the key citations. The back matter includes a timeline of statistical inventions." Another good resource for topics not included in the general texts listed previously.

## Experimental Design for Plant Biology

- Intuitive Biostatistics byCall Number: R 853 .S7 M68 2018ISBN: 9780190643560Publication Date: 2017"Takes a non-technical, non-quantitative approach to statistics and emphasizes interpretation of statistical results rather than the computational strategies for generating statistical data."
- The Analysis of Biological Data byCall Number: QH 323.5 .W48 2009 TEXTBOOKSISBN: 9780981519401Publication Date: 2008The authors "motivate learning with interesting biological and medical examples; they emphasize intuitive understanding; and they focus on real data. The book covers basic topics in introductory statistics, including graphs, confidence intervals, hypothesis testing, comparison of means, regression, and designing experiments." Available on reserves.
- Experimental Design for Biologists byCall Number: QH 323.5 .G565 2014ISBN: 9781621820413Publication Date: 2014"This handbook explains how to establish the framework for an experimental project, how to set up all of the components of an experimental system, design experiments within that system, determine and use the correct set of controls, and formulate models to test the veracity and resiliency of the data." A philosophical guide to experimental design, rather than a statistically focused approach.
- Experimental Design and Data Analysis for Biologists byCall Number: QH 323.5 .Q85 2002ISBN: 0521009766Publication Date: 2002"For students or researchers in biology who need to design experiments, sampling programs, or analyze resulting data. [...] The chapters include such topics as linear and logistic regression, simple and complex ANOVA models, log-linear models, and multivariate techniques. The main analyses are illustrated with many examples from published papers and an extensive reference list to both the statistical and biological literature is also included."

- Springer ProtocolsProvides access to full text reproducible laboratory protocols in the life and biomedical sciences.
- Protocols.io"Create and discover reproducible experimental and computational methods with video, reagents, detailed parameters, and more."

## Quantitative Research Methods

- Experiment! byISBN: 0470688254Publication Date: 2012"Provides an excellent introduction to the methodology and implementation of experimentation in the natural, engineering and medical sciences. [...] This book focuses on general research skills, such as adopting a scientific mindset, learning how to plan meaningful experiments and understanding the fundamentals of collecting and interpreting data. It is directed to anyone engaged in experiments." Particularly suitable for undergraduates or other novice researchers learning about designing their own experiments.
- Dealing with Statistics byCall Number: HA 29 .B76 2008ISBN: 0335227244Publication Date: 2007"The tools to choose the graphs and statistics that are suitable for your data, and to understand what the statistical results actually mean." A very short introduction to statistics and why you need to use them. It also includes some guidance on gathering data, focused for the social sciences, but the principles are broadly applicable.
- Statistics and Scientific Method byCall Number: Q 180.55 .S7 D54ISBN: 9780199543182Publication Date: 2011"Studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts." Recommended if you are considering designing an experiment but want a broad overview before choosing an approach, or if you have an approach but want to understand how it fits into the broader statistical and scientific thought process. The text is organized around case studies for different methods. It will likely be most applicable for undergraduates or graduate students learning about experimental design and who are comfortable with seeing equations scattered throughout the text.

## Experimental Design for Ecology and Evolutionary Biology

- Analysing Ecological Data byISBN: 1281044679Publication Date: 2007"The first part of the book gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modelling techniques), multivariate analysis, time series analysis (e.g. common trends) and spatial statistics. The second part provides 17 case studies, mainly written together with biologists who attended courses given by the first authors. [...] The case studies can be used as a template for your own data analysis; just try to find a case study that matches your own ecological questions and data structure, and use this as starting point for you own analysis."
- A Primer of Ecological Statistics byCall Number: QH 541.15 .S72 G68 2013ISBN: 9781605350646Publication Date: 2012"Explains fundamental material in probability theory, experimental design, and parameter estimation for ecologists and environmental scientists. "
- The Ecological Detective byCall Number: Oklahoma Biological Station Stacks QH 541.15 .M3 H54 1997ISBN: 0691034966Publication Date: 1997"The Ecological Detective makes liberal use of computer programming for the generation of hypotheses, exploration of data, and the comparison of different models. The authors' attitude is one of exploration, both statistical and graphical."
- Handbook of Meta-Analysis in Ecology and Evolution byCall Number: QH 541.15 .S72 H36 2013ISBN: 0691137293Publication Date: 2013"The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets."

## Repeated Measures Designs

- Mixed Effects Models and Extensions in Ecology with R byISBN: 1282036130Publication Date: 2009-01-01"Real data sets from postgraduate ecological studies or research projects are used throughout. The first part of the book is a largely non-mathematical introduction to linear mixed effects modelling, GLM and GAM, zero inflated models, GEE, GLMM and GAMM. The second part provides ten case studies that range from koalas to deep sea research."
- Mixed Effects Models in S and S-Plus byISBN: 1280145811Publication Date: 2000"This book provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data." It focuses in the NLME library for S and S-plus, but can be used in R, and the principles applied to other mixed-effect model packages such as lme4. The first few chapters are useful as an introduction to the topic and the remainder of the book will be of more interest to those with advanced modeling needs or interest in the mathematics of the modeling.

## Bayesian Statistics

- Bayesian Models byISBN: 1400866553Publication Date: 2015"This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods--in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians."
- Bayesian Inference byCall Number: QA 279.5 .L56 2010ISBN: 9780123748546Publication Date: 2010"This text is written to provide a mathematically sound [...] introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context." Available in a physical copy or an ebook.