Essential Math for Data Science

Python Data Science Handbook provides a reference to the solutions of commonly seen computational problems for both traditional and data scientists who use Python to enable their research. These scie

Ngorongoro Conservation Area in the heart of Maasailand is one of the world's most important conservation heritage areas. This book centres on a field study of the Ngorongoro Maasai and their herds, a

Master how to use the Julia language to solve business critical data science challenges. After covering the importance of Julia to the data science community and several essential data science princip

PRACTICAL PROBLEMS IN MATHEMATICS FOR HEALTH SCIENCE CAREERS, 3RD EDITION familiarizes readers in Allied Health programs with essential math processes using real-life examples and straightforward inst

Discover the fundamental principles of biomedical measurement design and performance evaluation with this hands-on guide. Whether you develop measurement instruments or use them in novel ways, this practical text will prepare you to be an effective generator and consumer of biomedical data. Designed for both classroom instruction and self-study, it explains how information is encoded into recorded data and can be extracted and displayed in an accessible manner. Describes and integrates experimental design, performance assessment, classification, and system modelling. Combines mathematical concepts with computational models, providing the tools needed to answer advanced biomedical questions. Includes MATLAB® scripts throughout to help readers model all types of biomedical systems, and contains numerous homework problems, with a solutions manual available online. This is an essential text for advanced undergraduate and graduate students in bioengineering, electrical and computer engineer

Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine le

An essential guide to healthcare data problems, sources, and solutionsStrategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing delu

Each book in this unique Math Mastery collection developed by experts covers all the essential skills for children in the first stages of their math journey. Each topic is supported by clear examples and helpful hints to encourage proficiency.Aimed at children aged 8-9, topics include numbers, counting, addition and subtraction, time and shape, measuring, and math practice. This collection is attractively illustrated and led by appealing characters who offer helpful tips to children (and parents) that make learning accessible and interesting. Every child can learn Math with Math Mastery.

Each book in this unique Math Mastery collection developed by experts covers all the essential skills for children in the first stages of their math journey. Each topic is supported by clear examples and helpful hints to encourage proficiency.Aimed at children aged 10-11, topics include numbers, counting, addition and subtraction, time and shape, measuring, and math practice. This collection is attractively illustrated and led by appealing characters who offer helpful tips to children (and parents) that make learning accessible and interesting. Every child can learn Math with Math Mastery.

Each book in this unique Math Mastery collection developed by experts covers all the essential skills for children in the first stages of their math journey. Each topic is supported by clear examples and helpful hints to encourage proficiency.Aimed at children aged 9-10, topics include numbers, counting, addition and subtraction, time and shape, measuring, and math practice. This collection is attractively illustrated and led by appealing characters who offer helpful tips to children (and parents) that make learning accessible and interesting. Every child can learn Math with Math Mastery.

Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical learning, big data analytics, graph theory, and game theory, this is an essential resource for graduate students and researchers in academia and industry with backgrounds in power systems engineering, applied mathematics, and computer science.

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.

Essential Skills for Health Career Success strengthens the basic academic skills?such as reading, writing, science, and math?that students need for a successful career in healthcare. Used for a stand-

A unique introduction to the design, analysis, and presentation of scientific projects, this is an essential textbook for undergraduate majors in science and mathematics. The textbook gives an overview of the main methods used in scientific research, including hypothesis testing, the measurement of functional relationships, and observational research. It describes important features of experimental design, such as the control of errors, instrument calibration, data analysis, laboratory safety, and the treatment of human subjects. Important concepts in statistics are discussed, focusing on standard error, the meaning of p values, and use of elementary statistical tests. The textbook introduces some of the main ideas in mathematical modeling, including order-of-magnitude analysis, function fitting, Fourier transforms, recursion relations, and difference approximations to differential equations. It also provides guidelines on accessing scientific literature, and preparing scientific paper

An essential collection of essays for librarians looking to provide E-science programs and capabilities to their institutions.

Learn from home or on-the-go and navigate the wilderness of middle school level Math in this hands-on study guide that gives 6th-8th graders all the tools for success!Learning is an adventure inside or outside of the classroom with this highly illustrated, handy field guide that will help kids master the essential skills and lessons of middle school Math. With expert knowledge presented in a bold and fun format that’s easy to read and understand, students will learn, explore, and practice the techniques and tools behind geometry, algebra, and more!The How to Survive Middle School study guides tackle all the essential middle school subjects. Each book trains readers in critical thinking and problem-solving skills to help them become independent learners. The interactive text, full of helpful tips and techniques, and engaging illustrations makes this so much more than just a textbook!Series Overview: This new series will launch in Summer 2022 with five titles including Math, Science, US

What is a focus group? Why do we use them? When should we use them? When should we not? Focus Groups for the Social Science Researcher provides a step-by-step guide to undertaking focus groups, whether as a stand-alone method or alongside other qualitative or quantitative methods. It recognizes the challenges that focus groups encounter and provides tips to address them. The book highlights three unique, inter-related characteristics of focus groups. First, they are inherently social in form. Second, the data emerge organically through conversation; they are emic in nature. Finally, focus groups generate data at three levels of analysis: the individual, group, and interactive level. The book builds from these three characteristics to explain when focus groups can usefully be employed in different research designs. This is an essential text for students and researchers looking for a concise and accessible introduction to this important approach to data collection.

What is a focus group? Why do we use them? When should we use them? When should we not? Focus Groups for the Social Science Researcher provides a step-by-step guide to undertaking focus groups, whether as a stand-alone method or alongside other qualitative or quantitative methods. It recognizes the challenges that focus groups encounter and provides tips to address them. The book highlights three unique, inter-related characteristics of focus groups. First, they are inherently social in form. Second, the data emerge organically through conversation; they are emic in nature. Finally, focus groups generate data at three levels of analysis: the individual, group, and interactive level. The book builds from these three characteristics to explain when focus groups can usefully be employed in different research designs. This is an essential text for students and researchers looking for a concise and accessible introduction to this important approach to data collection.

Pragmatic and Adaptable Textbook Meets the Needs of Students and Instructors from Diverse FieldsNumerical analysis is a core subject in data science and an essential tool for applied mathematicians, e

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.

Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students will also gain the ability to create, read and critique statistical applications in their fields of inte