Digital library
Textbooks, references and open learning resources.
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Introductory Statistics
Douglas Shafer; Zhiyi Zhang · Saylor Foundation · 2012
In many introductory level courses today, teachers are challenged with the task of fitting in all of the core concepts of the course in a limited period of time. The Introductory Statistics teacher is no stranger to this challenge. To add to the difficulty, many textbooks contain an overabundance of material, which not only results in the need for further streamlining, but also in intimidated students. Shafer and Zhang wrote Introductory Statistics by using their vast teaching experience to present a complete look at introductory statistics topics while keeping in mind a realistic expectation with respect to course duration and students' maturity level. Over time the core content of this course has developed into a well-defined body of material that is substantial for a one-semester course. Shafer and Zhang believe that the students in this course are best served by a focus on that core material and not by an exposure to a plethora of peripheral topics. Therefore in writing Introduction to Statistics they have sought to present only the core concepts and use a wide-ranging set of exercises for each concept to drive comprehension. As a result Introduction to Statistics is a smaller and less intimidating textbook that trades some extended and unnecessary topics for a better-focused presentation of the central material. You will not only appreciate the depth and breadth of exercises in Introduction to Statistics, but you will also like the close attention to detail that Shafer and Zhang have paid to the student and instructor solutions manuals. This is one of few books on the market where the textbook authors have written the solutions manuals to maintain the integrity of the material. In addition, in order to facilitate the use of technology with the book the authors included “large data set exercises,” where appropriate, that refer to large data sets that are available on the web, and for which use of statistical software is necessary.
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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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OpenIntro Statistics
David Diez; Christopher Barr; Mine Cetinkaya-Rundel · OpenIntro · 2019
OpenIntro Statistics covers a first course in statistics, providing a rigorous introduction to appliedstatistics that is clear, concise, and accessible. This book was written with the undergraduate levelin mind, but it’s also popular in high schools and graduate courses.We hope readers will take away three ideas from this book in addition to forming a foundationof statistical thinking and methods. • Statistics is an applied field with a wide range of practical applications.• You don’t have to be a math guru to learn from real, interesting data.• Data are messy, and statistical tools are imperfect. But, when you understand the strengthsand weaknesses of these tools, you can use them to learn about the world.
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Book of Proof
Richard Hammack · Richard Hammack · 2018
This is a book about how to prove theorems. Until this point in your education, you may have regarded mathematics primarily as a computational discipline. You have learned to solve equations, compute derivatives and integrals, multiply matrices and find determinants; and you have seen how these things can answer practical questions about the real world. In this setting, your primary goal in using mathematics has been to compute answers. But there is another approach to mathematics that is more theoretical than computational. In this approach, the primary goal is to understand mathematical structures, to prove mathematical statements, and even to invent or discover new mathematical theorems and theories. The mathematical techniques and procedures that you have learned and used up until now have their origins in this theoretical side of mathematics. For example, in computing the area under a curve, you use the fundamental theorem of calculus. It is because this theorem is true that your answer is correct. However, in your calculus class you were probably far more concerned with how that theorem could be applied than in understanding why it is true. But how do we know it is true? How can we convince ourselves or others of its validity? Questions of this nature belong to the theoretical realm of mathematics. This book is an introduction to that realm. This book will initiate you into an esoteric world. You will learn and apply the methods of thought that mathematicians use to verify theorems,explore mathematical truth and create new mathematical theories. This will prepare you for advanced mathematics courses, for you will be better able to understand proofs, write your own proofs and think critically and inquisitively about mathematics. This text has been used in classes at: Virginia Commonwealth University, Lebanon Valley College, University of California - San Diego, Colorado State University, Westminster College, South Dakota State University, PTEK College - Brunei,
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Fundamentals of Math, Physics, and Statistics for Future Transportation Professionals
Anurag Pande; Peyton Ratto; Ahmed Farid · Mavs Open Press · 2024
This textbook and OER material cover tools and basic knowledge required to master the prerequisite essentials of physics, mathematics, and statistics applied in transportation engineering. To our knowledge, no such textbook currently exists to build the KSTs (Knowledge, Skills, Tools) for college freshmen’ remedial courses required by most transportation engineering graduate programs that admit non-engineers (e.g., PHYS 141, MATH 142, STAT 321 at California Polytechnic State University, San Luis Obispo). The textbook modules are intended for students with undergraduate degrees in planning and other less technical fields who are interested in pursuing transportation careers where background engineering knowledge is required. This textbook is a product of 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 Probability
Charles Grinstead; J. Laurie Snell · American Mathematical Society · 2006
Probability theory began in seventeenth century France when the two great French mathematicians, Blaise Pascal and Pierre de Fermat, corresponded over two problems from games of chance. Problems like those Pascal and Fermat solved continuedto influence such early researchers as Huygens, Bernoulli, and DeMoivre in establishing a mathematical theory of probability. Today, probability theory is a wellestablished branch of mathematics that finds applications in every area of scholarlyactivity from music to physics, and in daily experience from weather prediction topredicting the risks of new medical treatments. This text is designed for an introductory probability course taken by sophomores,juniors, and seniors in mathematics, the physical and social sciences, engineering,and computer science. It presents a thorough treatment of probability ideas andtechniques necessary for a form understanding of the subject. The text can be usedin a variety of course lengths, levels, and areas of emphasis. For use in a standard one-term course, in which both discrete and continuousprobability is covered, students should have taken as a prerequisite two terms ofcalculus, including an introduction to multiple integrals. In order to cover Chapter 11, which contains material on Markov chains, some knowledge of matrix theoryis necessary. The text can also be used in a discrete probability course. The material has beenorganized in such a way that the discrete and continuous probability discussions arepresented in a separate, but parallel, manner. This organization dispels an overlyrigorous or formal view of probability and o?ers some strong pedagogical valuein that the discrete discussions can sometimes serve to motivate the more abstractcontinuous probability discussions. For use in a discrete probability course, studentsshould have taken one term of calculus as a prerequisite. Very little computing background is assumed or necessary in order to obtain fullbenefits from the use of the comp
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Υπολογιστική Φυσική: Ένα βιβλίο του Κωνσταντίνου Αναγνωστόπουλου
Κωνσταντίνος Αναγνωστόπουλος · National Technical University of Athens · 2016
Το βιβλίο αυτό είναι μια εισαγωγή στις υπολογιστικές μεθόδους που χρησιμοποιούνται στη φυσική και άλλα επιστημονικά πεδία. Απευθύνεται σε κοινό που έχει ήδη εκτεθεί σε μαθήματα γενικής φυσικής που διδάσκονται στα δύο πρώτα έτη πανεπιστημιακών τμημάτων θετικών επιστημών και επιστημών του μηχανικού. Δεν υποθέτει κανένα υπόβαθρο αριθμητικής ανάλυσης, προγραμματισμού ή χρήσης υπολογιστή και παρουσιάζει ό,τι είναι απαραίτητο για την επίλυση των προβλημάτων που παρουσιάζονται στο βιβλίο. Μπορεί να χρησιμοποιηθεί ως κύριο σύγγραμμα σε εισαγωγικά μαθήματα υπολογιστικής φυσικής και επιστημονικού προγραμματισμού. Το βιβλίο ξεκινάει με πολύ απλά προβλήματα πάνω στην κίνηση σωματιδίου και ολοκληρώνεται με μία εις βάθος συζήτηση προχωρημένων μεθόδων προσομοίωσης Μόντε Κάρλο στη στατιστική φυσική. Το επίπεδο διδασκαλίας είναι διαβαθμισμένο ως προς τη δυσκολία του, παρουσιάζοντας προβλήματα όπως η εξίσωση διάχυσης, δυναμικά συστήματα, ηλεκτροστατική στο επίπεδο, κβαντομηχανική και οι τυχαίες διαδρομές. Όλο το υλικό που παρουσιάζεται στο βιβλίο μπορεί να διαδαχθεί άνετα σε δύο εξάμηνα. Με κατάλληλη επιλογή θεμάτων, μπορεί να χρησιμοποιηθεί και σε ένα πλήρες μάθημα ενός εξαμήνου. Το βιβλίο αποσκοπεί να δώσει στους φοιτητές το υπόβαθρο και την εμπειρία που απαιτείται ώστε να προχωρήσουν σε προγράμματα υπολογισμών υψηλής απόδοσης. Δίνει έμφαση στον εμπειρικό προγραμματισμό αριθμητικών προγραμμάτων, αλλά και στην παραγωγή, ανάλυση και φυσική ερμηνεία των δεδομένων. Επίσης γίνεται προσπάθεια να διατηρηθεί το ενδιαφέρον του αναγνώστη μέσα από την παρουσίαση της αριθμητικής επίλυσης γνωστών και ενδιαφέροντων προβλημάτων φυσικής, οπως χαοτικών συστημάτων, κβαντομηχανικής, ειδικής θεωρίας της σχετικότητας και της φυσικής των μεταβάσεων φάσης. Το βιβλίο και το συνοδευτικό λογισμικό δίνονται ελεύθερα, αδειοδοτούμενα υπό Creative Commons License/GNU public License.
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Calculo diferencial e integral
Marta Bonacina; Claudia Teti; Alejandra Haidar · LATIn Project · 2014
Esta comunidad tiene como fin construir un texto base, que pretende ser la puerta de entrada al mundo de las matemáticas superiores y sus aplicaciones en el campo de las Ciencias de la Ingeniería.
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Thermodynamics and Introduction to Quantum Mechanics
Cathrine Southern · DePaul University
In the contents: 10: Appendix- Mathematics for Physical Chemistry
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Quantway Core
Carnegie Math Pathways · WestEd
Quantway Core provides a one-term introductory quantitative reasoning course solution that builds algebraic and quantitative skills and reasoning. It is designed to replace the developmental sequence and can also be used to fulfill high school and technical college program math requirements.
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Calculus
Gilbert Strang & Edwin Herman · MIT & University of Wisconsin-Stevens Point
In the contents: 4.08: Applied Optimization Problems
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ENVS C100: Environmental Science
Tanya Hoerer · Coastline College
In the contents: 1.2.04: Basic and Applied Science · 1.03: Math Blast- An Overview of Essential Mathematics Used in Science · 2.6.04: Applied Systems Toxicology
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Elementary Algebra
Wade Ellis & Denny Burzynski · LibreTexts
In the contents: 12.04: The 5-Step Method of Solving Applied Problems
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Calculus I: Differential Calculus
Doli Bambhania, Rani Fischer, Lisa Mesh & Danny Tran · De Anza College
In the contents: 4.08: Applied Optimization Problems
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Math 140: Calculus 1
Debbie Gaydos · Penn State University, Greater Allegheny
In the contents: 4.05: Applied Optimization Problems
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MAT 2410: Calculus 1
Peggy Beck · Prince George's Community College
In the contents: 4.08: Applied Optimization Problems
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Calculus
Eric Hutchinson · College of Southern Nevada
In the contents: 4.06: Applied Optimization Problems
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Math C180: Calculus I
Chau D Tran · Coastline College
In the contents: 4.07: Applied Optimization Problems
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Calculus for Engineering Technology
Vismar Jay Alfaro · University of Science and Technology of Southern Philippines- Jasaan
In the contents: 15.08: Applied Optimization Problems · 16.10: Applied Optimization
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Environmental Science
Melissa Ha and Rachel Schleiger · Yuba College & Butte College
In the contents: 1.2.04: Basic and Applied Science · 1.03: Math Blast- An Overview of Essential Mathematics Used in Science