Digital library
Textbooks, references and open learning resources.
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Creating Literary Analysis
LibreTexts · LibreTexts
In the contents: 3.10: Student Sample Paper- Sarah Davids A Lacanian Analysis of Nathaniel Hawthornes The Birthmark · 10.02: Chapter 3- Psychoanalysis
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Introduction to Economic Analysis
Anonymous · LibreTexts
In the contents: 1.03: Economic Reasoning and Analysis · 15.02: Basic Analysis
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Laboratory Manual - DC Electrical Circuit Analysis
James M. Fiore · Mohawk Valley Community College
In the contents: 13: Nodal Analysis · 14: Mesh Analysis
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Introduction to Real Analysis
William F. Trench · Trinity University
This book introduces readers to a rigorous understanding of mathematical analysis and presents challenging math concepts as clearly as possible. This book is intended for those who want to gain an understanding of mathematical analysis and challenging mathematical concepts.
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Thermal Methods of Analysis
Prabha Shetty · Sophia College for Women
In the contents: 01: Thermal Analysis · 03: Differential Thermal Analysis
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Mathematical Analysis
Elias Zakon · University of Windsor
This 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.
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Algorithm Design and Analysis
Godfry Justo · African Virtual University
In the contents: 01: Fundamental Design and Analysis Techniques · 1.01: Activity 1 - Overview of Algorithm Design and Analysis
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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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Social Data Analysis
Mikaila Arthur; Roger Clark · Rhode Island College Digital Publishing · 2021
Social data analysis enables you, as a researcher, to organize the facts you collect during your research. Your data may have come from a questionnaire survey, a set of interviews, or observations. They may be data that have been made available to you from some organization, national or international agency or other researchers. Whatever their source, social data can be daunting to put together in a way that makes sense to you and others. This book is meant to help you in your initial attempts to analyze data. In doing so it will introduce you to ways that others have found useful in their attempts to organize data. You might think of it as like a recipe book, a resource that you can refer to as you prepare data for your own consumption and that of others. And, like a recipe book that teaches you to prepare simple dishes, you may find this one pretty exciting. Analyzing data in a revealing way is at least as rewarding, we’ve found, as it is to cook up a yummy cashew carrot paté or a steaming corn chowder. We’d like to share our pleasure with you.
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Economic Policy Analysis Playbook
Leonie Pearson · University of Canberra · 2026
Economic Policy Analysis Playbook shows how policy actually works—moving beyond theory to a practical “playbook” for designing and evaluating decisions. Blending incentives, analytical tools, and global cases, it equips readers to test, challenge, and defend policy choices in complex real-world contexts.
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Introduction to Economic Analysis
Preston McAfee; Tracy Lewis · Saylor Foundation · 2009
This book presents standard intermediate microeconomics material and some material that, in the authors' view, ought to be standard but is not. Introductory economics material is integrated. Standard mathematical tools, including calculus, are used throughout. The book easily serves as an intermediate microeconomics text, and can be used for a relatively sophisticated undergraduate who has not taken a basic university course in economics. The focus of this book is on the conceptual tools and not on fluff. As such, it reflects the approach actually adopted by the majority of economists for understanding economic activity. There are lots of models and equations, and no pictures of economists ;-) Economic analysis is used in many situations. When British Petroleum sets the price for Alaskan crude oil, it uses an estimated demand model, both for gasoline consumers and also for the refineries to which BP sells. Economic analysis was used by experts in the antitrust suit brought by the U.S. Department of Justice both to understand Microsoft's incentive to foreclose (eliminate from the market) rival Netscape and consumer behavior in the face of alleged foreclosure. Stock market analysts use economic models to forecast the profits of companies to predict the price of their stocks. When the government forecasts the budget deficit or considers a change in environmental regulations, it uses economic models. This book presents the building blocks of the models in common use by an army of economists thousands of times per day. This book, plus econometrics, provides most of the economic analysis tools to take upper division economics courses of any type.
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Big Data for Epidemiology: Applied Data Analysis Using National Health Surveys
Tiffany Kindratt · Mavs Open Press · 2022
National data sets provide an avenue for students to practice data analytic skills while also answering meaningful research questions. This open education resource was developed to train future public health professionals how to conduct secondary data analysis of national health surveys using SAS statistical software. SAS software was selected because it is one of the most commonly used software programs used among public health departments and academia. The book includes details on how to analyze public-use data from five common national health surveys, including the National Health Interview Survey (NHIS), Medical Expenditure Panel Survey (MEPS), Health Information National Trends Survey (HINTS), Behavior Risk Factor Surveillance System (BRFSS) and National Health and Nutrition and Examination Survey (NHANES). All datasets and corresponding syntax files are available from the Open ICPSR Data Repository.
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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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Tea Time Numerical Analysis
Leon Brin · Leon Q. Brin · 2016
This textbook was born of a desire to contribute a viable, free, introductory Numerical Analysis textbook for instructors and students of mathematics. The ultimate goal of Tea Time Numerical Analysis is to be a complete, one-semester, single-pdf, downloadable textbook designed for mathematics classes. Now includes differential equations. Over 350 pages Over 1000 lines of code Over 200 figures Open source
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First Semester in Numerical Analysis with Julia
Giray Ökten · Florida State University · 2023
First Semester in Numerical Analysis with Julia presents the theory and methods, together with the implementation of the algorithms using the Julia programming language (version 1.1.0). The book covers computer arithmetic, root-finding, numerical quadrature and differentiation, and approximation theory. The reader is expected to have studied calculus and linear algebra. Some familiarity with a programming language is beneficial, but not required. The programming language Julia will be introduced in the book. The simplicity of Julia allows bypassing the pseudocode and writing a computer code directly after the description of a method while minimizing the distraction the presentation of a computer code might cause to the flow of the main narrative.
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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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Data Analysis in the Psychological Sciences: A Practical, Applied, Multimedia Approach
Leyre Castro; J. Toby Mordkoff · University of Iowa Libraries · 2023
This open resources textbook contains 10 Units that describe and explain the main concepts in statistical analysis of psychological data. In addition to conceptual descriptions and explanations of the basic analyses for descriptive statistics, this textbook also explains how to conduct those analyses with common statistical software (Excel) and open-source free software (R).
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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.