Essential Mathematics and Statistics for Science PDF Download
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Author: Dr. Graham Currell
Publisher: Wiley
ISBN: 9780470022290
Category : Science
Languages : en
Pages : 0
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Book Description
Basic Mathematics and Statistics for Science is a low-level introduction to the essential techniques students need to understand. It assumes little prior knowledge, and adopts a gentle approach that leads through examples in the book and website. No other text provides this range of educational support for science students. The integration between book and website provides study options that would be impossible through a book alone, and allows students to study in ways that suit their own circumstances and preferences. The combination of book and website also provides ready-prepared material for lectures, tutorials and computer practicals. Tutors can use the material to develop a variety of coherent programme using different learning styles. The book develops the mathematics and statistics through examples and questions that reflect the scientific context, and has succeeded in being relevant to a range of undergraduate science programmes.
Author: Dr. Graham Currell
Publisher: Wiley
ISBN: 9780470022290
Category : Science
Languages : en
Pages : 0
Get Book Here
Book Description
Basic Mathematics and Statistics for Science is a low-level introduction to the essential techniques students need to understand. It assumes little prior knowledge, and adopts a gentle approach that leads through examples in the book and website. No other text provides this range of educational support for science students. The integration between book and website provides study options that would be impossible through a book alone, and allows students to study in ways that suit their own circumstances and preferences. The combination of book and website also provides ready-prepared material for lectures, tutorials and computer practicals. Tutors can use the material to develop a variety of coherent programme using different learning styles. The book develops the mathematics and statistics through examples and questions that reflect the scientific context, and has succeeded in being relevant to a range of undergraduate science programmes.
Author: Craig Adam
Publisher: John Wiley & Sons
ISBN: 1119964180
Category : Medical
Languages : en
Pages : 298
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Book Description
This text is an accessible, student-friendly introduction to the wide range of mathematical and statistical tools needed by the forensic scientist in the analysis, interpretation and presentation of experimental measurements. From a basis of high school mathematics, the book develops essential quantitative analysis techniques within the context of a broad range of forensic applications. This clearly structured text focuses on developing core mathematical skills together with an understanding of the calculations associated with the analysis of experimental work, including an emphasis on the use of graphs and the evaluation of uncertainties. Through a broad study of probability and statistics, the reader is led ultimately to the use of Bayesian approaches to the evaluation of evidence within the court. In every section, forensic applications such as ballistics trajectories, post-mortem cooling, aspects of forensic pharmacokinetics, the matching of glass evidence, the formation of bloodstains and the interpretation of DNA profiles are discussed and examples of calculations are worked through. In every chapter there are numerous self-assessment problems to aid student learning. Its broad scope and forensically focused coverage make this book an essential text for students embarking on any degree course in forensic science or forensic analysis, as well as an invaluable reference for post-graduate students and forensic professionals. Key features: Offers a unique mix of mathematics and statistics topics, specifically tailored to a forensic science undergraduate degree. All topics illustrated with examples from the forensic science discipline. Written in an accessible, student-friendly way to engage interest and enhance learning and confidence. Assumes only a basic high-school level prior mathematical knowledge.
Author: K. A. Stroud
Publisher:
ISBN: 9780831133917
Category : Mathematics
Languages : en
Pages : 0
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Book Description
This is an entry level text for a wide range of courses in computer science, medicine, health sciences, social sciences, business, engineering and science. Using the phenomenally successful approach of the bestselling Engineering Mathematics by the same authors, it takes you through the math step-by-step with a wealth of examples and exercises. It is an appropriate refresher or brush-up for sci-tech and business students whose math skills need further development. Offers a unique module approach that takes users through the mathematics in a step-by-step fashion with a wealth of worked examples and exercises. Contains Quizzes, Learning Outcomes and Can You? Checklists that guide readers through each topic and focus understanding. Ideal as reference or a self-learning manual.
Author: Jeff Gill
Publisher: Cambridge University Press
ISBN: 0521834260
Category : Mathematics
Languages : en
Pages : 449
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Book Description
"More than ever before, modern social scientists require a basic level of mathematical literacy, yet many students receive only limited mathematical training prior to beginning their research careers. This textbook addresses this dilemma by offering a comprehensive, unified introduction to the essential mathematics of social science. Throughout the book the presentation builds from first principles and eschews unnecessary complexity. Most importantly, the discussion is thoroughly and consistently anchored in real social science applications, with more than 80 research-based illustrations woven into the text and featured in end-of-chapter exercises. Students and researchers alike will find this first-of-its-kind volume to be an invaluable resource."--BOOK JACKET.
Author: Brian Albright
Publisher: Jones & Bartlett Publishers
ISBN: 144968534X
Category : Mathematics
Languages : en
Pages : 607
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Book Description
This text combines the topics generally found in main-stream elementary statistics books with the essentials of the underlying theory. The book begins with an axiomatic treatment of probability followed by chapters on discrete and continuous random variables and their associated distributions. It then introduces basic statistical concepts including summarizing data and interval parameter estimation, stressing the connection between probability and statistics. Final chapters introduce hypothesis testing, regression, and non-parametric techniques. All chapters provide a balance between conceptual understanding and theoretical understanding of the topics at hand.
Author: Peter Bruce
Publisher: "O'Reilly Media, Inc."
ISBN: 1491952911
Category : Computers
Languages : en
Pages : 322
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Book Description
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Author: Erin N. Bodine
Publisher: Princeton University Press
ISBN: 0691150729
Category : Mathematics
Languages : en
Pages : 630
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Book Description
An accessible undergraduate textbook on the essential math concepts used in the life sciences The life sciences deal with a vast array of problems at different spatial, temporal, and organizational scales. The mathematics necessary to describe, model, and analyze these problems is similarly diverse, incorporating quantitative techniques that are rarely taught in standard undergraduate courses. This textbook provides an accessible introduction to these critical mathematical concepts, linking them to biological observation and theory while also presenting the computational tools needed to address problems not readily investigated using mathematics alone. Proven in the classroom and requiring only a background in high school math, Mathematics for the Life Sciences doesn't just focus on calculus as do most other textbooks on the subject. It covers deterministic methods and those that incorporate uncertainty, problems in discrete and continuous time, probability, graphing and data analysis, matrix modeling, difference equations, differential equations, and much more. The book uses MATLAB throughout, explaining how to use it, write code, and connect models to data in examples chosen from across the life sciences. Provides undergraduate life science students with a succinct overview of major mathematical concepts that are essential for modern biology Covers all the major quantitative concepts that national reports have identified as the ideal components of an entry-level course for life science students Provides good background for the MCAT, which now includes data-based and statistical reasoning Explicitly links data and math modeling Includes end-of-chapter homework problems, end-of-unit student projects, and select answers to homework problems Uses MATLAB throughout, and MATLAB m-files with an R supplement are available online Prepares students to read with comprehension the growing quantitative literature across the life sciences A solutions manual for professors and an illustration package is available
Author: Norman Matloff
Publisher: CRC Press
ISBN: 0429687117
Category : Business & Economics
Languages : en
Pages : 289
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Book Description
Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks. * Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture." * Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner. Prerequisites are calculus, some matrix algebra, and some experience in programming. Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.
Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446
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Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Author: Teresa Bradley
Publisher: John Wiley & Sons
ISBN: 1118358295
Category : Business & Economics
Languages : en
Pages : 693
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Book Description
Essential Mathematics for Economics and Business is established as one of the leading introductory textbooks on mathematics for students of business and economics. Combining a user–friendly approach to mathematics with practical applications to the subjects, the text provides students with a clear and comprehensible guide to mathematics. The fundamental mathematical concepts are explained in a simple and accessible style, using a wide selection of worked examples, progress exercises and real–world applications. New to this Edition Fully updated text with revised worked examples and updated material on Excel and Powerpoint New exercises in mathematics and its applications to give further clarity and practice opportunities Fully updated online material including animations and a new test bank The fourth edition is supported by a companion website at www.wiley.com/college/bradley, which contains: Animations of selected worked examples providing students with a new way of understanding the problems Access to the Maple T.A. test bank, which features over 500 algorithmic questions Further learning material, applications, exercises and solutions. Problems in context studies, which present the mathematics in a business or economics framework. Updated PowerPoint slides, Excel problems and solutions. "The text is aimed at providing an introductory-level exposition of mathematical methods for economics and business students. In terms of level, pace, complexity of examples and user-friendly style the text is excellent - it genuinely recognises and meets the needs of students with minimal maths background." —Colin Glass, Emeritus Professor, University of Ulster "One of the major strengths of this book is the range of exercises in both drill and applications. Also the 'worked examples' are excellent; they provide examples of the use of mathematics to realistic problems and are easy to follow." —Donal Hurley, formerly of University College Cork "The most comprehensive reader in this topic yet, this book is an essential aid to the avid economist who loathes mathematics!" —Amazon.co.uk
