tag:open.umn.edu,2005:/opentextbooks/subjects/35?page=3Open Textbook Library - Applied Textbooks2019-05-15T23:37:43Zhttps://open.umn.edu/assets/common/favicon/favicon-1594c2156c95ca22b1a0d803d547e5892bb0e351f682be842d64927ecda092e7.icohttps://open.umn.edu/assets/library/otl_logo-f9161d5c999f5852b38260727d49b4e7d7142fc707ec9596a5256a778f957ffc.png7102019-05-15T23:37:43Z2024-03-05T02:11:42ZFirst Semester in Numerical Analysis with Julia<img alt="Read more about First Semester in Numerical Analysis with Julia" title="First Semester in Numerical Analysis with Julia cover image" class="cover " width="155" height="200" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NjU2LCJwdXIiOiJibG9iX2lkIn19--ad942b5e610404311068b8a80f91f2b196c098d3/0000FSNumAnJu.jpg" />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.6732019-02-24T19:47:05Z2024-01-22T14:52:16ZYet Another Introductory Number Theory Textbook (Cryptology Emphasis Version)<img alt="Read more about Yet Another Introductory Number Theory Textbook (Cryptology Emphasis Version)" title="Yet Another Introductory Number Theory Textbook (Cryptology Emphasis Version) cover image" class="cover " width="657" height="848" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NjE3LCJwdXIiOiJibG9iX2lkIn19--c135223b353db201633704e27c7d3d27aeab8c1a/0000YetAnoCry.png" />This version of YAINTT has a particular emphasis on connections to cryptology. The cryptologic material appears in Chapter 4 and §§5.5 and 5.6, arising naturally (I hope) out of the ambient number theory. The main cryptologic applications – being the RSA cryptosystem, Diffie-Hellman key exchange, and the ElGamal cryptosystem – come out so naturally from considerations of Euler’s Theorem, primitive roots, and indices that it renders quite ironic G.H. Hardy’s assertion [Har05] of the purity and eternal inapplicability of number theory. Note, however, that once we broach the subject of these cryptologic algorithms, we take the time to make careful definitions for many cryptological concepts and to develop some related ideas of cryptology which have much more tenuous connections to the topic of number theory. This material therefore has something of a different flavor from the rest of the text – as is true of all scholarly work in cryptology (indeed, perhaps in all of computer science), which is clearly a discipline with a different culture from that of “pure”mathematics. Obviously, these sections could be skipped by an uninterested reader, or remixed away by an instructor for her own particular class approach.6422018-11-17T23:55:20Z2024-01-22T14:52:06ZBusiness Math: A Step-by-Step Handbook<img alt="Read more about Business Math: A Step-by-Step Handbook" title="Business Math: A Step-by-Step Handbook cover image" class="cover " width="1275" height="1650" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6Mjc3OSwicHVyIjoiYmxvYl9pZCJ9fQ==--efbe7d78f26171d06a6f77beca690afef66ca5cb/Lyryx_Business%20Math_2021B.jpg" />Business Mathematics was written to meet the needs of a twenty-first century student. It takes a systematic approach to helping students learn how to think and centers on a structured process termed the PUPP Model (Plan, Understand, Perform, and Present). This process is found throughout the text and in every guided example to help students develop a step-by-step problem-solving approach. This textbook simplifies and integrates annuity types and variable calculations, utilizes relevant algebraic symbols, and is integrated with the Texas Instruments BAII+ calculator. It also contains structured exercises, annotated and detailed formulas, and relevant personal and professional applications in discussion, guided examples, case studies, and even homework questions.5592018-09-07T17:22:10Z2024-01-22T14:52:15ZLearning Statistics with R: A tutorial for psychology students and other beginners<img alt="Read more about Learning Statistics with R: A tutorial for psychology students and other beginners" title="Learning Statistics with R: A tutorial for psychology students and other beginners cover image" class="cover " width="700" height="350" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NDgyLCJwdXIiOiJibG9iX2lkIn19--fd748bcb52ebaa08c105c5a6410ea1ae4ed6e56e/0000LearStatR.png" />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.5492018-09-07T17:22:09Z2024-01-22T14:52:20ZIntroductory Statistics with Randomization and Simulation - First Edition<img alt="Read more about Introductory Statistics with Randomization and Simulation - First Edition" title="Introductory Statistics with Randomization and Simulation - First Edition cover image" class="cover " width="400" height="500" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NDczLCJwdXIiOiJibG9iX2lkIn19--525c81372a81a6a06bdcd9744cd02899e5289a3f/0000IntroStat.png" />We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods. (1) Statistics is an applied field with a wide range of practical applications. (2) You don't have to be a math guru to learn from interesting, real data. (3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world. Textbook overview The chapters of this book are as follows:1. Introduction to data. Data structures, variables, summaries, graphics, and basic data collection techniques.2. Foundations for inference. Case studies are used to introduce the ideas of statistical inference with randomization and simulations. The content leads into the standard parametric framework, with techniques reinforced in the subsequent chapters.1It is also possible to begin with this chapter and introduce tools from Chapter 1 as theyare needed.3. Inference for categorical data. Inference for proportions using the normal and chi-square distributions, as well as simulation and randomization techniques.4. Inference for numerical data. Inference for one or two sample means using the t distribution, and also comparisons of many means using ANOVA. A special section for bootstrapping is provided at the end of the chapter.5. Introduction to linear regression. An introduction to regression with two variables. Most of this chapter could be covered immediately after Chapter 1.6. Multiple and logistic regression. An introduction to multiple regression and logistic regression for an accelerated course. Appendix A. Probability. An introduction to probability is provided as an optional reference. Exercises and additional probability content may be found in Chapter 2 of OpenIntro Statistics at openintro.org. Instructor feedback suggests that probability, if discussed, is best introduced at the very start or very end of the course.5522018-09-07T17:22:09Z2024-01-22T14:51:58ZAdvanced High School Statistics - 2nd Edition<img alt="Read more about Advanced High School Statistics - 2nd Edition" title="Advanced High School Statistics - 2nd Edition cover image" class="cover " width="386" height="499" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NjY5LCJwdXIiOiJibG9iX2lkIn19--b702cce8198a6135936867e6a4f7dbaef1d3ed04/hs-stats2.jpg" />We hope readers will take away three ideas from this book in addition to forming a foundationof statistical thinking and methods. (1) Statistics is an applied field with a wide range of practical applications. (2) You don't have to be a math guru to learn from real, interesting data. (3) Data are messy, and statistical tools are imperfect. But, when you understand the strengths and weaknesses of these tools, you can use them to learn about the real world. Textbook overviewThe chapters of this book are as follows: 1. Data collection. Data structures, variables, and basic data collection techniques. 2. Summarizing data. Data summaries and graphics. 3. Probability. The basic principles of probability. 4. Distributions of random variables. Introduction to key distributions, and how the normal model applies to the sample mean and sample proportion. 5. Foundation for inference. General ideas for statistical inference in the context of estimating the population proportion. 6. Inference for categorical data. Inference for proportions using the normal and chisquare distributions. 7. Inference for numerical data. Inference for one or two sample means using the t distribution, and comparisons of many means using ANOVA. 8. Introduction to linear regression. An introduction to regression with two variables. Instructions are also provided in several sections for using Casio and TI calculators.5332018-09-07T17:22:08Z2024-01-22T14:52:06ZLinear Algebra with Applications<img alt="Read more about Linear Algebra with Applications" title="Linear Algebra with Applications cover image" class="cover " width="612" height="792" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6MjIwMCwicHVyIjoiYmxvYl9pZCJ9fQ==--a5e9704092f548c6111e89cafe7e2c051b838513/Nicholson-LAWA-2021A-Thumbnail.png" />After being traditionally published for many years, this formidable text by W. Keith Nicholson is now being released as an open educational resource and part of Lyryx with Open Texts! Supporting today's students and instructors requires much more than a textbook, which is why Dr. Nicholson opted to work with Lyryx Learning. Overall, the aim of the text is to achieve a balance among computational skills, theory, and applications of linear algebra. It is a relatively advanced introduction to the ideas and techniques of linear algebra targeted for science and engineering students who need to understand not only how to use these methods but also gain insight into why they work. The contents have enough flexibility to present a traditional introduction to the subject, or to allow for a more applied course. Chapters 1–4 contain a one-semester course for beginners whereas Chapters 5–9 contain a second semester course. The text is primarily about real linear algebra with complex numbers being mentioned when appropriate (reviewed in Appendix A).5092018-09-07T17:22:07Z2024-01-22T14:52:01ZIntroductory Business Statistics<img alt="Read more about Introductory Business Statistics" title="Introductory Business Statistics cover image" class="cover " width="496" height="496" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NDM2LCJwdXIiOiJibG9iX2lkIn19--4e5040f49870b1a40bb5cec6c2f9449058a4db17/9781947172470.png" />Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.5182018-09-07T17:22:07Z2024-01-22T14:52:00ZCalculo diferencial e integral<img alt="Read more about Calculo diferencial e integral" title="Calculo diferencial e integral cover image" class="cover " width="800" height="1131" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsiZGF0YSI6NDQ0LCJwdXIiOiJibG9iX2lkIn19--3f8dbd6268faf40ef2610547e20f8d7db2bb7441/0000CalDifInt.png" />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.4592018-09-07T17:22:03Z2024-01-22T14:51:55ZIntroduction to Statistics<img alt="Read more about Introduction to Statistics" title="textbook cover placeholder image" class="cover fallback " width="247" height="326" data-controller="common--cover" data-placeholder="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" src="/assets/common/placeholder-0e0607cbc50663ddb9e8fd188058bcd2630c730ef6ee322801278607b7d5af8e.png" />Introduction to Statistics is a resource for learning and teaching introductory statistics. This work is in the public domain. Therefore, it can be copied and reproduced without limitation. However, we would appreciate a citation where possible. Please cite as: Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University. Instructor's manual, PowerPoint Slides, and additional questions are available.
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