tag:open.umn.edu,2005:/opentextbooks/subjects/mathematicsOpen Textbook Library - Mathematics Textbooks2024-03-17T02:21:08Zhttps://open.umn.edu/assets/common/favicon/favicon-1594c2156c95ca22b1a0d803d547e5892bb0e351f682be842d64927ecda092e7.icohttps://open.umn.edu/assets/library/otl_logo-f9161d5c999f5852b38260727d49b4e7d7142fc707ec9596a5256a778f957ffc.png16252024-03-17T02:29:08Z2024-03-18T16:57:08ZStatistics Through an Equity Lens<img alt="Read more about Statistics Through an Equity Lens" title="Statistics Through an Equity Lens cover image" class="cover " width="350" height="453" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTEzMzksInB1ciI6ImJsb2JfaWQifX0=--6fa5edfb6f4b03ea5cb23131acbda0189aa9f165/081622_RotelProject_Statistics2-002-350x453.jpg" />This Open Educational Resource (OER) carries a significant responsibility by presenting statistics through an equity lens. The metaphor of a lens is used intentionally–as the glasses one wears can have a profound effect on what one sees. The book encourages further inspection of the ways in which data is collected, interpreted, and analyzed on a variety of social justice issues, such as health disparities, hunger and food insecurity, homelessness, behavioral health (mental health and substance use), and incarceration of males of color. It also attempts to reveal how the misuse of data can reinforce inequities, for example, by stigmatizing people and labeling neighborhoods as high poverty, violent, and having poor educational opportunities. Whether an intended or unintended consequence, irresponsible data use can contribute to racist impressions of people and communities.16102024-03-04T00:54:46Z2024-03-04T00:55:31ZBusiness Calculus with Excel<img alt="Read more about Business Calculus with Excel" title="Business Calculus with Excel cover image" class="cover " width="727" height="939" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTEyMzUsInB1ciI6ImJsb2JfaWQifX0=--84274e3eac03a3fc6b37c07b2279e23c8588b9be/buscalc.jpg" />This text is intended for a one semester calculus course for business students with the equivalent of a college algebra prerequisite. Rather than being a three-semester engineering calculus course that has been watered down to fit into one semester it is designed for the business students.15882024-03-03T20:42:21Z2024-03-03T20:42:21ZStatistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models<img alt="Read more about Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models" title="Statistics for Ecologists: A Frequentist and Bayesian Treatment of Modern Regression Models cover image" class="cover " width="271" height="350" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTExNjUsInB1ciI6ImJsb2JfaWQifX0=--feffe8e765afc8a1f9d23bb6640fd9aa537179a0/Statistics4Ecologists.pdf.jpg" />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.15682024-01-14T05:10:05Z2024-01-14T05:10:05ZElementos básicos de Análisis Inteligente de Datos<img alt="Read more about Elementos básicos de Análisis Inteligente de Datos" title="Elementos básicos de Análisis Inteligente de Datos cover image" class="cover " width="1129" height="1600" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTA2NTcsInB1ciI6ImJsb2JfaWQifX0=--3f5feea96d7a74bb13f369cb811bb74be917f510/submission_65_65_coverImage_es_ES.jpg" />Este libro trata sobre conceptos elementales junto con scripts cortos de código basado en R Project para hacer análisis inteligente de datos. La relación entre la teoría y la práctica es fundamental en la comprensión de una disciplina, así la aplicación de procedimientos y funciones específicas en tareas elementales es el propósito de este texto. La idea central del texto tiene origen en la asignatura denominada “Análisis Inteligente de Datos”, una cátedra en la que el profesor aporta con elementos fundamentales basados en conceptos y ejercicios prácticos usando R Project. Hoy en día, la disponibilidad de herramientas para la minería de datos es sin duda muy grande. Usuarios con conocimientos básicos pueden aprovechar de utilitarios intuitivos implementados en poderosos entornos de desarrollo. Nosotros hemos querido dar un enfoque al texto hacia una audiencia con mayor relación a la programación y software. Específicamente que constituya una guía básica para estudiantes que inician en el campo de la Inteligencia de datos.15672024-01-14T05:04:37Z2024-01-14T05:04:37ZProcesos de producción de tilapias (Oreochromis niloticus) con aplicación informática<img alt="Read more about Procesos de producción de tilapias (Oreochromis niloticus) con aplicación informática" title="Procesos de producción de tilapias (Oreochromis niloticus) con aplicación informática cover image" class="cover " width="1129" height="1600" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTA2NTIsInB1ciI6ImJsb2JfaWQifX0=--699b887eb3a2320182d0db33bd8a2f5e452ce889/submission_64_64_coverImage_es_ES.jpg" />El manuscrito se centra en el desarrollo de un software para optimizar la producción de tilapias, abordando aspectos como el crecimiento, costo y rentabilidad. Utilizando herramientas tecnológicas avanzadas, se pretende facilitar la gestión de datos para los piscicultores, permitiendo procesos más eficientes, económicos y precisos. Los factores clave incluyen el peso, la temperatura, el crecimiento absoluto, el crecimiento térmico de los peces, y proyecciones mensuales de costos, producción y rentabilidad. El software, desarrollado en Java y utilizando la plataforma Eclipse, busca equilibrar agilidad y precisión en el tratamiento de datos. El trabajo se apoya en la revisión bibliográfica y entrevistas con piscicultores. Se emplea un enfoque de análisis de componentes principales y correlación de Pearson para asociar variables relevantes. Se evalúa la aplicación mediante datos históricos y pruebas piloto, ajustando funcionalidades para garantizar resultados fiables. Se destaca la importancia de interfaces amigables para usuarios no expertos en tecnología y se propone la expansión a aplicaciones móviles y la adaptación a otras especies de interés zootécnico.15352023-11-29T21:26:53Z2023-11-29T21:26:53ZCounting Rocks! An Introduction to Combinatorics<img alt="Read more about Counting Rocks! An Introduction to Combinatorics" title="Counting Rocks! An Introduction to Combinatorics cover image" class="cover " width="728" height="942" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTAzMzAsInB1ciI6ImJsb2JfaWQifX0=--eb3782cd964d2ef6822caf90bedf86970954e958/counting%20rocks.jpg" />This textbook, Counting Rocks!, is the written component of an interactive introduction to combinatorics at the undergradaute level. Throughout the text, we link to videos where we describe the material and provide examples; see the Youtube playlist on the Colorado State University (CSU) Mathematics YouTube channel. The major topics in this text are counting problems (Chapters 1-4), proof techniques (Chapter 5), recurrence relations and generating functions (Chapters 6-7), and graph theory (Chapters 8-12). The material and the problems we include are standard for an undergraduate combinatorics course. In this text, one of our goals was to describe the mathematical structures underlying problems in combinatorics. For example, we separate the description of sequences, permutations, sets and multisets in Chapter 3. In addition to the videos, we would like to highlight some other features of this book. Most chapters contain an investigation section, where students are led through a series of deeper problems on a topic. In several sections, we show students how to use the free online computing software SAGE in order to solve problems; this is especially useful for the problems on recurrence relations. We have included many helpful figures throughout the text, and we end each chapter (and many of the sections) with a list of exercises of varying difficulty.15372023-11-01T18:40:49Z2023-12-25T15:28:38ZUn Análisis Científico del Ruido Ambiental y Laboral en Sectores Urbanos<img alt="Read more about Un Análisis Científico del Ruido Ambiental y Laboral en Sectores Urbanos" title="Un Análisis Científico del Ruido Ambiental y Laboral en Sectores Urbanos cover image" class="cover " width="1131" height="1600" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTAyNTksInB1ciI6ImJsb2JfaWQifX0=--0c3efee1cc50118aa410c8b8c63c1db8c104a4aa/submission_50_50_coverImage_es_ES.jpg" />¿Cuál es el nivel de ruido existente Av. Av. 3 de Julio y sus intersecciones entre la calle Ambato y la Y del Indio Colorado de la ciudad de Santo Domingo?, el presente trabajo de investigación tiene como objetivo principal conocer el nivel de ruido existente en este sector de la ciudad, con el fin de determinar el alcance de su afectación y sobre todo sus fuentes, se realizó la evaluación correspondiente de acuerdo con la normativa TULSMA. y Decreto Ejecutivo N° 2393, aplicando la investigación de campo se midió la presencia de ruido ambiental y ocupacional, se requirió del uso de dosímetros calibrados y certificados para obtener información precisa. En esta investigación se estudió estas importantes intersecciones, siendo que, en cuanto a normativa ambiental sobrepasa el nivel tolerable con un diferencial de 10 decibeles en promedio, mientras que en referencia del ruido laboral esta intersección está por debajo de los niveles permisibles con al menos 9 decibeles en promedio, las posibles enfermedades subyacentes más comunes encontradas fueron el estrés, los dolores de cabeza que afectaban principalmente a la población comerciante permanente, y la actividad que mayor emisión de ruido produjo fue el tránsito vehicular, del mismo modo se identificó que el día que se produjo mayor contaminación acústica fue el sábado entre las 11:30 am hasta la 13:00 pm.15292023-10-25T03:02:42Z2023-10-25T03:04:18ZIntroduction to Probability<img alt="Read more about Introduction to Probability" title="Introduction to Probability cover image" class="cover " width="736" height="957" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MTAxNDQsInB1ciI6ImJsb2JfaWQifX0=--eeb1f0bad95a9ba2f0020f6595ad1b23f5a4d974/Screenshot%202023-10-24%20at%209.50.32%20PM.png" />This is an introduction to probability theory, designed for self-study. It covers the same topics as the one-semester introductory courses which I taught at the University of Minnesota, with some extra discussion for reading on your own. The reasons which underlie the rules of probability are emphasized. Probability theory is certainly useful. But how does it feel to study it? Well, like other areas of mathematics, probability theory contains elegant concepts, and it gives you a chance to exercise your ingenuity, which is often fun. But in addition, randomness and probability are part of our experience in the real world, present everywhere and yet still somewhat mysterious. This gives the subject of probability a special interest.15102023-10-15T22:29:52Z2023-10-16T23:42:47ZPolimetrics: A Stata Companion to Introduction to Political Science Research Methods - 1st Edition<img alt="Read more about Polimetrics: A Stata Companion to Introduction to Political Science Research Methods - 1st Edition" title="Polimetrics: A Stata Companion to Introduction to Political Science Research Methods - 1st Edition cover image" class="cover " width="608" height="788" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6OTg4NiwicHVyIjoiYmxvYl9pZCJ9fQ==--884d3e8dfd3a69c08105e507eb9de39c342b97f7/Screenshot%202023-10-15%20at%205.13.07%20PM.png" />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.14962023-09-28T22:32:41Z2023-10-09T14:28:37ZClassical Numerical Methods in Scientific Computing<img alt="Read more about Classical Numerical Methods in Scientific Computing" title="Classical Numerical Methods in Scientific Computing cover image" class="cover " width="300" height="350" data-controller="cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6OTU4OCwicHVyIjoiYmxvYl9pZCJ9fQ==--735b24851aa129204bfdb36cb407784bc4c1ce3c/submission_67_84_coverImage_en_US_t.png" />Partial differential equations are paramount in mathematical modelling with applications in engineering and science. The book starts with a crash course on partial differential equations in order to familiarize the reader with fundamental properties such as existence, uniqueness and possibly existing maximum principles. The main topic of the book entails the description of classical numerical methods that are used to approximate the solution of partial differential equations. The focus is on discretization methods such as the finite difference, finite volume and finite element method. The manuscript also makes a short excursion to the solution of large sets of (non)linear algebraic equations that result after application of discretization method to partial differential equations. The book treats the construction of such discretization methods, as well as some error analysis, where it is noted that the error analysis for the finite element method is merely descriptive, rather than rigorous from a mathematical point of view. The last chapters focus on time integration issues for classical time-dependent partial differential equations. After reading the book, the reader should be able to derive finite element methods, to implement the methods and to judge whether the obtained approximations are consistent with the solution to the partial differential equations. The reader will also obtain these skills for the other classical discretization methods. Acquiring such fundamental knowledge will allow the reader to continue studying more advanced methods like meshfree methods, discontinuous Galerkin methods and spectral methods for the approximation of solutions to partial differential equations.
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