Digital library
Textbooks, references and open learning resources.
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Analytical Chemistry 2.1
David Harvey · David T. Harvey · 2016
As currently taught in the United States, introductory courses in analytical chemistry emphasize quantitative (and sometimes qualitative) methods of analysis along with a heavy dose of equilibrium chemistry. Analytical chemistry, however, is much more than a collection of analytical methods and an understanding of equilibrium chemistry; it is an approach to solving chemical problems. Although equilibrium chemistry and analytical methods are important, their coverage should not come at the expense of other equally important topics. The introductory course in analytical chemistry is the ideal place in the undergraduate chemistry curriculum for exploring topics such as experimental design, sampling, calibration strategies, standardization, optimization, statistics, and the validation of experimental results. Analytical methods come and go, but best practices for designing and validating analytical methods are universal. Because chemistry is an experimental science it is essential that all chemistry students understand the importance of making good measurements. My goal in preparing this textbook is to find a more appropriate balance between theory and practice, between “classical” and “modern” analytical methods, between analyzing samples and collecting samples and preparing them for analysis, and between analytical methods and data analysis. There is more material here than anyone can cover in one semester; it is my hope that the diversity of topics will meet the needs of different instructors, while, perhaps, suggesting some new topics to cover.
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Forest Measurements: An Applied Approach
Joan DeYoung · Open Oregon Educational Resources · 2016
This is a forest measurements textbook written for field technicians. Silvicultural applications and illustrations are provided to demonstrate the relevance of the measurements. Special “technique tips” for each skill are intended to help increase data collection accuracy and confidence. These include how to avoid common pitfalls, effective short cuts and essentials for recording field data correctly. The emphasis is on elementary skills; it is not intended to be a timber cruising guide.
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Food Preparation Lab Manual for FSHN 1150
Erica Beirman; Kate Gilbert; ISU Department of Food Science and Human Nutrition · Iowa State University Digital Press · 2025
This lab book is intended for use in both the lab and kitchen. Each section of the book contains learning objectives, lab problems to be solved, recipes, questions, and observation charts for the input of data. This book is aligned with the introductory Food Preparation Laboratory course at Iowa State University.
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Basic Scientific Food Preparation Lab Manual
Iowa State University Department of Food Science and Human Nutrition · Iowa State University Digital Press · 2023
This lab book is intended for use in both the lab and kitchen. Each section of the book contains learning objectives, lab problems to be solved, recipes, questions, and observation charts for the input of data.
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Statistics with JASP: First Steps for Psychology Students
Rebecca Denniss; Stanislava Naneva · University of Sheffield · 2025
New to statistics software? This guide is designed just for you. Whether you are studying psychology or any subject that involves analysing data, this easy-to-follow introduction to JASP will help you get to grips with the basics—no previous experience needed. Originally written for first-year psychology students at the University of Sheffield, it walks you through everything from entering data and adjusting settings to running t-tests, correlations, and chi-square analyses. With clear explanations, practical tips, and helpful screenshots, this guide makes learning JASP simple and stress-free.
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Learning Statistics with jamovi: A Tutorial for Beginners in Statistical Analysis
Danielle Navarro; David Foxcroft · Open Book Publishers · 2025
Based on Danielle Navarro’s widely acclaimed and prize-winning book Learning Statistics with R, this elegantly designed textbook offers undergraduate students a thorough and accessible introduction to jamovi, as well as how to get to grips with statistics and data manipulation. Lucid and easy to understand, Learning Statistics with jamovi covers the analysis of contingency tables, t-tests, correlation, regression, ANOVA and factor analysis, while also giving students a firm grounding in descriptive statistics and graphing. It includes learning aids for applying statistical principles using the jamovi interface, as well as embedded data files to accompany the book, and comprehensive chapters on probability theory, sampling and estimation, and null hypothesis testing. Freely available in open access, Learning Statistics with jamovi is an ideal introduction for undergraduate and postgraduate students of psychology, as well as behavioural and health science students and anyone who needs to understand and use statistical analysis in their work.
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Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models
John Fieberg · University of Minnesota Libraries Publishing · 2024
Ecological data pose many challenges to statistical inference. Most data come from observational studies rather than designed experiments; observational units are frequently sampled repeatedly over time, resulting in multiple, non-independent measurements; response data are often binary (e.g., presence-absence data) or non-negative integers (e.g., counts), and therefore, the data do not fit the standard assumptions of linear regression (Normality, independence, and constant variance). This book will familiarize readers with modern statistical methods that address these complexities using both frequentist and Bayesian frameworks.
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Polimetrics: A Stata Companion to Introduction to Political Science Research Methods
Josh Franco · Open Political Science (OPoliSci) · 2021
Polimetrics: A Stata Companion, authored by Dr. Josh Franco, is an Open Education Resource workbook licensed CC BY-NC and designed as a Stata companion to Introduction to Political Science Research Methods. This workbook provides a tour of the Stata software, an introduction to cross-sectional, time series, and panel data, and an introduction to a variety of models. I review models where the outcome is linear, binary, ordinal, categorical, and count. Additionally, I have an interpretation chapter on survival models. Each “Models” chapter has a similar organizational structure: about, estimated time, what is the model, how are models run in Stata, how do we interpret the model results, and a real-world example of model results in a Creative Commons licensed, peer-reviewed journal article. Additionally, mini-assignment instructions and a rubric are included so students can practice their interpretation skills.
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Foundations of Biomedical Science: Quantitative Literacy: Theory and Problems
Julian Pakay · La Trobe University · 2023
Foundations of Biomedical Science: Quantitative Literacy Theory and Problems is designed to help students develop the fundamental mathematical and quantitative literacy required to navigate and interpret evidence-based Biomedical data. This will provide students with the skills and confidence to habitually question any quantitative data they come across and to use these skills to make informed judgements regarding their veracity.
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COMPUTATIONAL PHYSICS: A Practical Introduction to Computational Physics and Scientific Computing (using C++)
Konstantinosn Anagnostopoulos · National Technical University of Athens · 2016
This book is an introduction to the computational methods used in physics, but also in other scientific fields. It is addressed to an audience that has already been exposed to the introductory level of college physics, usually taught during the first two years of an undergraduate program in science and engineering. It assumes no prior knowledge of numerical analysis, programming or computers and teaches whatever is necessary for the solution of the problems addressed in the text. It can be used as a textbook in introductory computational physics or scientific computing classes. The book starts with very simple problems in particle motion and ends with an in-depth discussion of advanced techniques used in Monte Carlo simulations in statistical mechanics. The level of instruction rises slowly, while discussing problems like the diffusion equation, electrostatics on the plane, quantum mechanics and random walks. All the material can be taught in two semesters, but a selection of topics can form the material of a one semester course. The book aims to provide the students with the background and the experience needed in order to advance to high performance computing projects in science and engineering. It puts emphasis on hands--on programming of numerical code but also on the production, analysis and interpretation of data. But it also tries to keep the students motivated by considering interesting applications in physics, like chaos, quantum mechanics, special relativity and the physics of phase transitions. There is a C++ and a Fortran edition for the core programming. Data analysis is performed using the powerful tools of the GNU/Linux environment. All the necessary software is open source and freely available. The book and the accompanying software are given under a Creative Commons License/GNU public License as a service to the community. It can be used freely as a whole, or any part of it, in any form, by anyone. There is no official distribution of hard copies, b
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Learning Statistics with R: A tutorial for psychology students and other beginners
Danielle Navarro · Danielle Navarro · 2018
Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.
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Calculus for the Life Sciences: A Modeling Approach
James Cornette; Ralph Ackerman · A.T. Still University · 2013
Our writing is based on three premises. First, life sciences students are motivated by and respond well to actual data related to real life sciences problems. Second, the ultimate goal of calculus in the life sciences primarily involves modeling living systems with difference and differential equations. Understanding the concepts of derivative and integral are crucial, but the ability to compute a large array of derivatives and integrals is of secondary importance. Third, the depth of calculus for life sciences students should be comparable to that of the traditional physics and engineering calculus course; else life sciences students will be short changed and their faculty will advise them to take the 'best' (engineering) course. In our text, mathematical modeling and difference and differential equations lead, closely follow, and extend the elements of calculus. Chapter one introduces mathematical modeling in which students write descriptions of some observed processes and from these descriptions derive first order linear difference equations whose solutions can be compared with the observed data. In chapters in which the derivatives of algebraic, exponential, or trigonometric functions are defined, biologically motivated differential equations and their solutions are included. The chapter on partial derivatives includes a section on the diffusion partial differential equation. There are two chapters on non-linear difference equations and on systems of two difference equations and two chapters on differential equations and on systems of differential equation.
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Calculus for the Life Sciences: A Modeling Approach
James Cornette; Ralph Ackerman · A.T. Still University · 2011
Our writing is based on three premises. First, life sciences students are motivated by and respond well to actual data related to real life sciences problems. Second, the ultimate goal of calculus in the life sciences primarily involves modeling living systems with difference and differential equations. Understanding the concepts of derivative and integral are crucial, but the ability to compute a large array of derivatives and integrals is of secondary importance. Third, the depth of calculus for life sciences students should be comparable to that of the traditional physics and engineering calculus course; else life sciences students will be short changed and their faculty will advise them to take the 'best' (engineering) course. In our text, mathematical modeling and difference and differential equations lead, closely follow, and extend the elements of calculus. Chapter one introduces mathematical modeling in which students write descriptions of some observed processes and from these descriptions derive first order linear difference equations whose solutions can be compared with the observed data. In chapters in which the derivatives of algebraic, exponential, or trigonometric functions are defined, biologically motivated differential equations and their solutions are included. The chapter on partial derivatives includes a section on the diffusion partial differential equation. There are two chapters on non-linear difference equations and on systems of two difference equations and two chapters on differential equations and on systems of differential equation.
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Introduction to Sociology
Tonja Conerly; Kathleen Holmes; Asha Tamang · OpenStax · 2021
Introduction to Sociology 3e aligns to the topics and objectives of many introductory sociology courses. It is arranged in a manner that provides foundational sociological theories and contexts, then progresses through various aspects of human and societal interactions. The new edition is focused on driving meaningful and memorable learning experiences related to critical thinking about society and culture. The text includes comprehensive coverage of core concepts, discussions and data relevant to a diverse audience, and features that draw learners into the discipline in powerful and personal ways. Overall, Introduction to Sociology 3e aims to center the course and discipline as crucial elements for understanding relationships, society, and civic engagement; the authors seek to lay the foundation for students to apply what they learn throughout their lives and careers. The authors, reviewers, and the entire team worked to build understanding of the causes and impacts of discrimination and prejudice. Introduction to Sociology 3e contains dozens of examples of discrimination and its outcomes regarding social science, society, institutions, and individuals. The text seeks to strike a balance between confronting the damaging aspects of our culture and history and celebrating those who have driven change and overcome challenges. The core discussion of these topics are present in Chapter 11 on Race and Ethnicity, and Chapter 12 on Gender, Sex, and Sexuality, but their causes and effects are extensively discussed in the context of other topics, including education, law enforcement, government, healthcare, the economy, and so on. Together and when connected by an instructor, these elements have potential for deep and lasting effects.
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Introduction to Systems Biology: Workbook for Flipped-Classroom Teaching
Thomas Sauter; Marco Albrecht · Open Book Publishers · 2023
This book is an introduction to the language of systems biology, which is spoken among many disciplines, from biology to engineering. Authors Thomas Sauter and Marco Albrecht draw on a multidisciplinary background and evidence-based learning to facilitate the understanding of biochemical networks, metabolic modeling and system dynamics. Their pedagogic approach briefly highlights core ideas of concepts in a broader interdisciplinary framework to guide a more effective deep dive thereafter. The learning journey starts with the purity of mathematical concepts, reveals its power to connect biological entities in structure and time, and finally introduces physics concepts to tightly align abstraction with reality. This workbook is all about self-paced learning, supports the flipped-classroom concept, and kick-starts with scientific evidence on studying. Each chapter comes with links to external YouTube videos, learning checklists, and Integrated real-world examples to gain confidence in thinking across scientific perspectives. The result is an integrated approach that opens a line of communication between theory and application, enabling readers to actively learn as they read. This overview of capturing and analyzing the behavior of biological systems will interest adherers of systems biology and network analysis, as well as related fields such as bioinformatics, biology, cybernetics, and data science.
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Introduction to Biosystems Engineering
Nicholas M. Holden; Mary Leigh Wolfe; Jactone A. Ogejo; Enda J. Cummins · American Society of Agricultural and Biological Engineers (ASABE), Virginia Tech Publishing · 2021
The discipline of Biosystems Engineering emerged in the 1990s from the traditional strongholds of agricultural engineering and food engineering. Biosystems engineering integrates engineering science and design with applied biological, environmental, and agricultural sciences. Introduction to Biosystems Engineering is targeted at 1st and 2nd year university-level students with an interest in biosystems engineering but who are not yet familiar with the breadth and depth of the subject. It is designed as a coherent educational resource, also available for download as individual digital chapters. The book can be used as a localized, customizable text for introductory courses in Biosystems Engineering globally. It is written as a series of stand-alone chapters organized under six major topics: Food and Bioprocessing; Environment; Buildings and Infrastructure; Information and Communications Technology and Data; Machinery Systems; and Energy. Each chapter is organized around stated learning outcomes and describes key concepts, applications of the concepts, and worked examples. Instructors adopting or reviewing this text are encouraged to register with the publisher using this form.
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How To Do Science
Louise Lexis; Brianna Julien · University of Southern Queensland · 2022
'How To Do Science' has been written for students of the life sciences who are actively engaged in the scientific process. This guide introduces you to what it means to be a scientist. You will learn about the scientific method and how to carry out many tasks of a scientist, including: designing experiments, visualising data, accessing scientific literature, communicating science, and writing literature reviews.
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Introduction to Sociology 3e
Tonja R. Conerly; Kathleen Holmes; Asha Lal Tamang; Jennifer Hensley · OpenStax, Rice University
Introduction to Sociology 3e aligns to the topics and objectives of many introductory sociology courses. It is arranged in a manner that provides foundational sociological theories and contexts, then progresses through various aspects of human and societal interactions. The new edition is focused on driving meaningful and memorable learning experiences related to critical thinking about society and culture. The text includes comprehensive coverage of core concepts, discussions and data relevant to a diverse audience, and features that draw learners into the discipline in powerful and personal ways. Overall, Introduction to Sociology 3e aims to center the course and discipline as crucial elements for understanding relationships, society, and civic engagement; the authors seek to lay the foundation for students to apply what they learn throughout their lives and careers. The authors, reviewers, and the entire team worked to build understanding of the causes and impacts of discrimination and prejudice. Introduction to Sociology 3e contains dozens of examples of discrimination and its outcomes regarding social science, society, institutions, and individuals. The text seeks to strike a balance between confronting the damaging aspects of our culture and history and celebrating those who have driven change and overcome challenges. The core discussion of these topics are present in Chapter 11 on Race and Ethnicity, and Chapter 12 on Gender, Sex, and Sexuality, but their causes and effects are extensively discussed in the context of other topics, including education, law enforcement, government, healthcare, the economy, and so on. Together and when connected by an instructor, these elements have potential for deep and lasting effects. Changes made in Introduction to Sociology 3e are described in the preface to help instructors transition to the third edition. The second edition of Introduction to Sociology by OpenStax is available in web view here.
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Más allá de la digitalización: La necesidad de la transformación digital estratégica
Marcos Antonio Espinoza-Mina; Alejandra Mercedes Colina-Vargas · Editorial Grupo AEA · 2025
En la era actual de disrupción digital, impulsada por avances en IA, Big Data y cambios en las expectativas del cliente, la Transformación Digital Estratégica (TDE) es un imperativo que va más allá de la simple digitalización. Este texto ofrece una guía estratégica integral, basada en investigación académica y análisis de la industria, para navegar esta compleja transición. Se presenta la TDE como un fenómeno holístico y multifacético que requiere la integración coherente de estrategia, cultura organizacional y liderazgo transformador. Es crucial desarrollar agilidad y capacidades dinámicas para la adaptación e innovación continuas. Los pilares clave incluyen el alineamiento estratégico, la creación de valor digital centrado en el cliente, modelos de negocio adaptables, gestión de datos como activo, culturas ágiles y liderazgo digital. Se examina el rol de tecnologías habilitadoras como Cloud (agilidad), IA (eficiencia/personalización) y Analítica Avanzada (decisiones), enfocadas en generar valor empresarial, junto a IoT y Blockchain. El texto también aborda desafíos inherentes como resistencia cultural, ciberseguridad, privacidad y ética de la IA, extrayendo perspectivas de ejemplos y mejores prácticas. Dirigido a estudiantes y profesionales, proporciona un marco integrado, accionable y basado en evidencia para liderar una TDE exitosa y sostenible.
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SMC: Social Sciences Statistics
Bettina Spencer · Saint Mary's College
In the contents: 1.3: Presentation of Data · 02: Sampling and Data · 2.3: Data, Sampling, and Variation in Data and Sampling