Digital library
Textbooks, references and open learning resources.
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Public Policy: Origins, Practice, and Analysis
Kimberly Martin; Keith Lee Jr.; John Hall · University of North Georgia Press
Public Policy: Origins, Practice, and Analysis
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Mathematical Analysis I
Elias Zakon · The Trillia Group · 2004
This award-winning text carefully leads the student through the basic topics of Real Analysis. Topics include metric spaces, open and closed sets, convergent sequences, function limits and continuity, compact sets, sequences and series of functions, power series, differentiation and integration, Taylor's theorem, total variation, rectifiable arcs, and sufficient conditions of integrability. Well over 500 exercises (many with extensive hints) assist students through the material. For students who need a review of basic mathematical concepts before beginning "epsilon-delta"-style proofs, the text begins with material on set theory (sets, quantifiers, relations and mappings, countable sets), the real numbers (axioms, natural numbers, induction, consequences of the completeness axiom), and Euclidean and vector spaces; this material is condensed from the author's Basic Concepts of Mathematics, the complete version of which can be used as supplementary background material for the present text.
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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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Basic Statistics Using R for Crime Analysis
Jaeyoung Choi · The Pennsylvania Alliance for Design of Open Textbooks (PA-ADOPT) · 2024
Limited access to subscription-based statistical software poses obstacles when students want to apply the skills they acquired in college. Although students may learn programs like SPSS or Stata while at the university, they often find themselves unable to continue using these programs after graduation, making their acquired skills obsolete. As an open-source software program, R offers a solution to this challenge. It is freely accessible to anyone, including students, after they graduate. Therefore, I decided to write a freely available book for those interested in becoming crime analysts, focusing on learning statistics without delving too deeply into mathematics. Moreover, this book emphasizes practical applications by utilizing R for data analysis, ensuring students can develop relevant skills beyond the university. I hope that students can easily follow the instructions in this book and replicate the same outcomes using the provided data. This practical experience will demonstrate the value of statistics and R, ideally inspiring students to further their learning in these areas.
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Measure, Integration & Real Analysis
Sheldon Axler · Sheldon Axler · 2020
This book seeks to provide students with a deep understanding of the definitions, examples, theorems, and proofs related to measure, integration, and real analysis. The content and level of this book fit well with the first-year graduate course on these topics at most American universities. This textbook features a reader-friendly style and format that will appeal to today's students.
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A Primer of Real Analysis
Dan Sloughter · Dan Sloughter · 2009
This is a short introduction to the fundamentals of real analysis. Although the prerequisites are few, I have written the text assuming the reader has the level of mathematical maturity of one who has completed the standard sequence of calculus courses, has had some exposure to the ideas of mathematical proof (including induction), and has an acquaintance with such basic ideas as equivalence relations and the elementary algebraic properties of the integers.
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Introduction to Mathematical Analysis I
Beatriz Lafferriere; Gerardo Lafferriere; Mau Nam Nguyen · Portland State University Library · 2016
Our goal with this textbook is to provide students with a strong foundation in mathematical analysis. Such a foundation is crucial for future study of deeper topics of analysis. Students should be familiar with most of the concepts presented here after completing the calculus sequence. However, these concepts will be reinforced through rigorous proofs. The lecture notes contain topics of real analysis usually covered in a 10-week course: the completeness axiom, sequences and convergence, continuity, and differentiation. The lecture notes also contain many well-selected exercises of various levels. Although these topics are written in a more abstract way compared with those available in some textbooks, teachers can choose to simplify them depending on the background of the students. For instance, rather than introducing the topology of the real line to students, related topological concepts can be replaced by more familiar concepts such as open and closed intervals. Some other topics such as lower and upper semicontinuity, differentiation of convex functions, and generalized differentiation of non-differentiable convex functions can be used as optional mathematical projects. In this way, the lecture notes are suitable for teaching students of different backgrounds. The second edition includes a number of improvements based on recommendations from students and colleagues and on our own experience teaching the course over the last several years. In this edition we streamlined the narrative in several sections, added more proofs, many examples worked out in detail, and numerous new exercises. In all we added over 50 examples in the main text and 100 exercises (counting parts).
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How We Got from There to Here: A Story of Real Analysis
Robert Rogers; Eugene Boman · Open SUNY · 2014
The typical introductory real analysis text starts with an analysis of the real number system and uses this to develop the definition of a limit, which is then used as a foundation for the definitions encountered thereafter. While this is certainly a reasonable approach from a logical point of view, it is not how the subject evolved, nor is it necessarily the best way to introduce students to the rigorous but highly non-intuitive definitions and proofs found in analysis. This book proposes that an effective way to motivate these definitions is to tell one of the stories (there are many) of the historical development of the subject, from its intuitive beginnings to modern rigor. The definitions and techniques are motivated by the actual difficulties encountered by the intuitive approach and are presented in their historical context. However, this is not a history of analysis book. It is an introductory analysis textbook, presented through the lens of history. As such, it does not simply insert historical snippets to supplement the material. The history is an integral part of the topic, and students are asked to solve problems that occur as they arise in their historical context. This book covers the major topics typically addressed in an introductory undergraduate course in real analysis in their historical order. Written with the student in mind, the book provides guidance for transforming an intuitive understanding into rigorous mathematical arguments. For example, in addition to more traditional problems, major theorems are often stated and a proof is outlined. The student is then asked to fill in the missing details as a homework problem.
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Introduction to Real Analysis
William Trench · A.T. Still University · 2013
This is a text for a two-term course in introductory real analysis for junior or senior mathematics majors and science students with a serious interest in mathematics. Prospective educators or mathematically gifted high school students can also benefit from the mathematical maturity that can be gained from an introductory real analysis course. The book is designed to fill the gaps left in the development of calculus as it is usually presented in an elementary course, and to provide the background required for insight into more advanced courses in pure and applied mathematics. The standard elementary calculus sequence is the only specific prerequisite for Chapters 1–5, which deal with real-valued functions. (However, other analysis oriented courses, such as elementary differential equation, also provide useful preparatory experience.) Chapters 6 and 7 require a working knowledge of determinants, matrices and linear transformations, typically available from a first course in linear algebra. Chapter 8 is accessible after completion of Chapters 1–5.
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Basic Analysis: Introduction to Real Analysis
Jirí Lebl · Jirí Lebl · 2016
This free online textbook (e-book in webspeak) is a one semester course in basic analysis. This book started its life as my lecture notes for Math 444 at the University of Illinois at Urbana-Champaign (UIUC) in the fall semester of 2009, and was later enhanced to teach Math 521 at University of Wisconsin-Madison (UW-Madison). A prerequisite for the course is a basic proof course. It should be possible to use the book for both a basic course for students who do not necessarily wish to go to graduate school, but also as a first semester of a more advanced course that also covers topics such as metric spaces.
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The Delft Method for System Dynamics
Willem Auping; Floortje d’Hont; Merla Kubli; Jill Slinger · TU Delft Open · 2024
The Delft Method for System Dynamics (SD) is a proven method for learning basic SD. The method focuses on learning by doing: first you try to work through an exercise, and if you do not understand something, then you can look up the theory. The book contains exercises on topics such as causal loop diagrams, delays, and when SD is an appropriate methodology. It also contains modelling exercises that show students how to build low to medium complexity models, and how to use these models for policy analysis. The theory chapters cover all phases of the modelling cycle: problem articulation, conceptualisation, formulation, evaluation (including validation and scenario analysis), and policy analysis. This book is intended for students and teachers in large or small System Dynamics courses, and for motivated students that want to learn SD at their own pace.
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Transportation Land Use Modeling and Policy (TLUMP)
Qisheng Pan; Soheil Sharifi-Asl · Mavs Open Press · 2024
Transportation Land Use Modeling and Policy is an open educational resource (OER) that offers a thorough exploration of various approaches and frameworks for modeling the complex relationship between land use and transportation, with a focus on scenario-based analysis for issues such as equity, environmental impact, and other critical transportation policies. The textbook begins by providing an overview of the current urban transportation landscape, highlighting ongoing challenges like transportation equity. It then introduces foundational theories related to land use and transportation, setting the stage for an in-depth examination of different modeling approaches. Using case studies and real-world examples, primarily from North America, the book demonstrates how these models explain and predict the relationship between land use (residential, economic, industrial activities) and transportation (accessibility). After reviewing existing integrated land use and transportation models and discussing the future direction of integrated land use and transportation planning, the latter part of the book delves deeper into travel demand modeling (TDM) practices. It highlights traditional methods like the four-step model and provides a brief overview of newer techniques such as activity- based and agent-based models. This textbook is part of a six-volume series produced under the grant OERTransport: Enabling Transportation Planning Professional Advancement awarded to the University of Texas-Arlington (UTA) in consortium with California Polytechnic State University (Cal Poly) and the University of South Florida (USF). It was developed under an Open Textbooks Pilot grant from the Fund for the Improvement of Postsecondary Education (FIPSE), U.S. Department of Education. However, its contents do not necessarily represent the policy of the Department of Education, and no endorsement by the Federal Government should be assumed.
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Introduction to Statistics in the Psychological Sciences
Linda Cote; Rupa Gordon; Chrislyn Randell; Judy Schmitt · University of Missouri - St. Louis · 2021
Introduction to Statistics in the Psychological Sciences provides an accessible introduction to the fundamentals of statistics, and hypothesis testing as need for psychology students. The textbook introduces the fundamentals of statistics, an introduction to hypothesis testing, and t Tests. Related samples, independent samples, analysis of variance, correlations, linear regressions and chi-squares are all covered along with expanded appendices with z, t, F correlation, and a Chi-Square table. The text includes key terms and exercises with answers to odd-numbered exercises. Psychology students often find statistics courses to be different from their other psychology classes. There are some distinct differences, especially involving study strategies for class success. The first difference is learning a new vocabulary—it is similar to learning a new language. Knowing the meaning of certain words will help as you are reading the material and working through the problems. Secondly, practice is critical for success; reading over the material is not enough. Statistics is a subject learned by doing, so make sure you work through any homework questions, chapter questions, and practice problems available. Statistical knowledge gives you a set of skills employable in graduate school and the workplace. Data science is a burgeoning field, and there is practical significance in learning this material. The statistics presented in this book are some of the most common ones used in research articles, and we hope by the end of this OER you’ll feel comfortable reading (and not skipping!) the results section of an article. This work is broken into 14 chapters, covering the fundamentals of statistics, and hypothesis testing.
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Introduction to Political Science Research Methods
Josh Franco; Charlotte Lee; Kau Vue · Academic Senate for California Community Colleges · 2020
Introduction to Political Science Research Methods, authored by Dr. Josh Franco, Dr. Charlotte Lee, Kau Vue, Dr. Dino Bozonelos, Dr. Masahiro Omae, and Dr. Steven Cauchon, is an Open Education Resource textbook licensed CC BY-NC that surveys the research methods employed in political science. The textbook includes chapters that cover: history and development of the empirical study of politics; the scientific method; theories, hypotheses, variables, and units; conceptualization, operationalization and measurement of political concepts; elements of research design including the logic of sampling; qualitative and quantitative research methods and means of analysis; and research ethics.
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Introduction to LGBTQ+ Studies: A Cross-Disciplinary Approach
Deborah Amory; Sean Massey; Jennifer Miller; Allison Brown · State University of New York Press · 2022
Designed for an introductory course, this textbook takes a cross-disciplinary approach to the study of LGBTQ+ issues that helps students grasp core concepts through a variety of different perspectives. Introduction to LGBTQ+ Studies offers accessible, academically sound information on a wide range of topics, including history, culture, and Queer Theory; an exploration of LGBTQ+ relationships, families, parenting, health, and education; and how to conduct research on LGBTQ+ topics. The book explores LGBTQ+ issues from the ancient world to contemporary global perspectives. Employing an intersectional analysis, the textbook highlights how sexuality and gender are simultaneously experienced and constructed through other structures of inequality and privilege, such as race and class. The text supports multiple learning styles by integrating visual elements, multimedia resources, discussion and project prompts, and resources for further research throughout the textbook.
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Research Methods for Criminal Justice Students
Monica Williams · Monica Williams · 2022
This book is based on two open-access textbooks: Bhattacherjee’s (2012) Social science research: Principles, methods, and practices and Blackstone’s (2012) Principles of sociological inquiry: Qualitative and quantitative methods. I first used Bhattacherjee’s book in a graduate-level criminal justice research methods course. I chose the book because it was an open educational resource that covered the major topics of my course. While I found the book adequate for my purposes, the business school perspective did not always fit with my criminal justice focus. I decided to rewrite the textbook for undergraduate and graduate students in my criminal justice research methods courses. As I researched other open- educational resources for teaching social science research methods, I found Blackstone’s book, which covered more of the social science and qualitative methods perspectives that I wanted to incorporate into my book. As a result, this open-access textbook includes some content from both previous works along with my own additions based on my extensive experience and expertise in conducting qualitative and quantitative research in social science settings and in mentoring students through the research process. My Ph.D. is in Sociology, and I currently teach undergraduates and graduate students in a criminal justice program at Weber State University. Throughout my career, I have conducted and published the results of research projects using a variety of methods, including surveys, case studies, in-depth interviews, participant observation, content analysis, and secondary analysis of quantitative data. I have also mentored undergraduates in conducting community-based research projects using many of these same methods with the addition of focus groups and program evaluations.
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Quantitative Research Methods for Political Science, Public Policy and Public Administration (With Applications in R)
Hank Jenkins-Smith; Joseph Ripberger · University of Oklahoma Libraries · 2017
The focus of this book is on using quantitative research methods to test hypotheses and build theory in political science, public policy and public administration. It is designed for advanced undergraduate courses, or introductory and intermediate graduate-level courses. The first part of the book introduces the scientific method, then covers research design, measurement, descriptive statistics, probability, inference, and basic measures of association. The second part of the book covers bivariate and multiple linear regression using the ordinary least squares, the calculus and matrix algebra that are necessary for understanding bivariate and multiple linear regression, the assumptions that underlie these methods, and then provides a short introduction to generalized linear models.The book fully embraces the open access and open source philosophies. The book is freely available in the SHAREOK repository; it is written in R Markdown files that are available in a public GitHub repository; it uses and teaches R and RStudio for data analysis, visualization and data management; and it uses publically available survey data (from the Meso-Scale Integrated Socio-geographic Network) to illustrate important concepts and methods. We encourage students to download the data, replicate the examples, and explore further! We also encourage instructors to download the R Markdown files and modify the text for use in different courses.
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Quantitative Methods for Plant Breeding
Walter Suza; Kendall Lamkey · Iowa State University Digital Press · 2023
This open textbook covers common statistics used in agriculture research, including experimental design in plant breeding and genetics, as well as the analysis of variance, regression, and correlation.
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Concept Development Studies in Chemistry
John Hutchinson · OpenStax CNX · 2013
This collection of Concept Development Studies in Chemistry is presented to redirect the focus of learning. In each concept development study, a major chemical concept is developed and refined by analysis of experimental observations and careful reasoning. Each study begins with the definition of an initial Foundation of assumed knowledge, followed by a statement of questions which arise from the Foundation. Analysis of these questions is presented as a series of observations and logical deductions, followed by further questions. This detailed process is followed until the conceptual development of a model provides a reasonable answer to the stated questions.
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Unfolding the Mystery of Life, Biology Lab Manual for Non-Science Majors
Ellen Genovesi; Laura Blinderman; Patrick Natale · Ellen Genovesi, Laura Blinderman and Patrick Natale · 2019
This laboratory manual is intended for use in a biology laboratory course taken by non-science majors, pre-biology, and pre-allied health majors. Laboratory exercises provide students with experience in basic laboratory skills, gathering and organizing data, measuring and calculating, hypothesis testing, analysis of data, writing, and laboratory safety. The skill sets are designed to promote the development of critical thought and analysis. Students work with living and preserved specimens, and laboratory reagents and equipment.