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Mathematics & science

See below for a selection of the latest books from Mathematics & science category. Presented with a red border are the Mathematics & science books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Mathematics & science books and those from many more genres to read that will keep you inspired and entertained. And it's all free!

Measurement Error in Longitudinal Data

Measurement Error in Longitudinal Data

Longitudinal data is essential for understanding how the world around us changes. Most theories in the social sciences and elsewhere have a focus on change, be it of individuals, of countries, of organizations, or of systems, and this is reflected in the myriad of longitudinal data that are being collected using large panel surveys. This type of data collection has been made easier in the age of Big Data and with the rise of social media. Yet our measurements of the world are often imperfect, and longitudinal data is vulnerable to measurement errors which can lead to flawed and misleading conclusions. Measurement Error in Longitudinal Data tackles the important issue of how to investigate change in the context of imperfect data. It compiles the latest advances in estimating change in the presence of measurement error from several fields and covers the entire process, from the best ways of collecting longitudinal data, to statistical models to estimate change under uncertainty, to examples of researchers applying these methods in the real world. This book introduces the essential issues of longitudinal data collection, such as memory effects, panel conditioning (or mere measurement effects), the use of administrative data, and the collection of multi-mode longitudinal data. It also presents some of the most important models used in this area, including quasi-simplex models, latent growth models, latent Markov chains, and equivalence/DIF testing. Finally, the use of vignettes in the context of longitudinal data and estimation methods for multilevel models of change in the presence of measurement error are also discussed.

Communicating with Data

Communicating with Data

Author: Deborah (Professor, Professor, University of California) Nolan, Sara Stoudt Format: Hardback Release Date: 10/03/2021

Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how to distill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a course with a writing component. Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extend the guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.

Communicating with Data

Communicating with Data

Author: Deborah (Professor, Professor, University of California) Nolan, Sara Stoudt Format: Paperback / softback Release Date: 10/03/2021

Communication is a critical yet often overlooked part of data science. Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data. General advice on science writing is also provided, including how to distill findings into a story and organize and revise the story, and how to write clearly, concisely, and precisely. This is an excellent resource for students who want to learn how to write about scientific findings, and for instructors who are teaching a science course in communication or a course with a writing component. Communicating with Data consists of five parts. Part I helps the novice learn to write by reading the work of others. Part II delves into the specifics of how to describe data at a level appropriate for publication, create informative and effective visualizations, and communicate an analysis pipeline through well-written, reproducible code. Part III demonstrates how to reduce a data analysis to a compelling story and organize and write the first draft of a technical paper. Part IV addresses revision; this includes advice on writing about statistical findings in a clear and accurate way, general writing advice, and strategies for proof reading and revising. Part V offers advice about communication strategies beyond the page, which include giving talks, building a professional network, and participating in online communities. This book also provides 22 portfolio prompts that extend the guidance and examples in the earlier parts of the book and help writers build their portfolio of data communication.

How to Get Your PhD

How to Get Your PhD

Author: Gavin (Professor, Professor, University of Manchester) Brown Format: Paperback / softback Release Date: 01/03/2021

A unique take on how to survive and thrive in the process your PhD, this is a book that stands out from the crowd of traditional PhD guides. Compiled by a leading UK researcher, and written in a highly personal one-to-one manner, How to Get Your PhD showcases the thoughts of diverse and distinguished minds hailing from the UK, EU, and beyond, spanning both academia and industry. With over 150 bitesize nuggets of actionable advice, it offers more detailed contributions covering topics such as career planning, professional development, diversity and inclusion in science, and the nature of risk in research. How to Get Your PhD: A Handbook for the Journey is as readable for people considering a PhD as it is for those in the middle of one: aiming to clarify the highs and lows that come when training in the profession of research, while providing tips & tricks for the journey. This concise yet complete guide allows students to dip in and read just what they need, rather than adding to the mountain of reading material they already have.

Insights from Data with R

Insights from Data with R

Experiments, surveys, measurements, and observations all generate data. These data can provide useful insights for solving problems, guiding decisions, and formulating strategy. Progressing from relatively unprocessed data to insight, and doing so efficiently, reliably, and confidently, does not come easily, and yet gaining insights from data is a fundamental skill for science as well as many other fields and often overlooked in most textbooks of statistics and data analysis. This accessible and engaging book provides readers with the knowledge, experience, and confidence to work with data and unlock essential information (insights) from data summaries and visualisations. Based on a proven and successful undergraduate course structure, it charts the journey from initial question, through data preparation, import, cleaning, tidying, checking, double-checking, manipulation, and final visualization. These basic skills are sufficient to gain useful insights from data without the need for any statistics; there is enough to learn about even before delving into that world! The book focuses on gaining insights from data via visualisations and summaries. The journey from raw data to insights is clearly illustrated by means of a comprehensive Workflow Demonstration in the book featuring data collected in a real-life study and applicable to many types of question, study, and data. Along the way, readers discover how to efficiently and intuitively use R, RStudio, and tidyverse software, learning from the detailed descriptions of each step in the instructional journey to progress from the raw data to creating elegant and informative visualisations that reveal answers to the initial questions posed. There are an additional three demonstrations online! Insights from Data with R is suitable for undergraduate students and their instructors in the life and environmental sciences seeking to harness the power of R, RStudio, and tidyverse software to master the valuable and prerequisite skills of working with and gaining insights from data.

Insights from Data with R

Insights from Data with R

Experiments, surveys, measurements, and observations all generate data. These data can provide useful insights for solving problems, guiding decisions, and formulating strategy. Progressing from relatively unprocessed data to insight, and doing so efficiently, reliably, and confidently, does not come easily, and yet gaining insights from data is a fundamental skill for science as well as many other fields and often overlooked in most textbooks of statistics and data analysis. This accessible and engaging book provides readers with the knowledge, experience, and confidence to work with data and unlock essential information (insights) from data summaries and visualisations. Based on a proven and successful undergraduate course structure, it charts the journey from initial question, through data preparation, import, cleaning, tidying, checking, double-checking, manipulation, and final visualization. These basic skills are sufficient to gain useful insights from data without the need for any statistics; there is enough to learn about even before delving into that world! The book focuses on gaining insights from data via visualisations and summaries. The journey from raw data to insights is clearly illustrated by means of a comprehensive Workflow Demonstration in the book featuring data collected in a real-life study and applicable to many types of question, study, and data. Along the way, readers discover how to efficiently and intuitively use R, RStudio, and tidyverse software, learning from the detailed descriptions of each step in the instructional journey to progress from the raw data to creating elegant and informative visualisations that reveal answers to the initial questions posed. There are an additional three demonstrations online! Insights from Data with R is suitable for undergraduate students and their instructors in the life and environmental sciences seeking to harness the power of R, RStudio, and tidyverse software to master the valuable and prerequisite skills of working with and gaining insights from data.

How to Think About Abstract Algebra

How to Think About Abstract Algebra

How to Think about Abstract Algebra provides an engaging and readable introduction to its subject, which encompasses group theory and ring theory. Abstract Algebra is central in most undergraduate mathematics degrees, and it captures regularities that appear across diverse mathematical structures - many people find it beautiful for this reason. But its abstraction can make its central ideas hard to grasp, and even the best students might find that they can follow some of the reasoning without really understanding what it is all about. This book aims to solve that problem. It is not like other Abstract Algebra texts and is not a textbook containing standard content. Rather, it is designed to be read before starting an Abstract Algebra course, or as a companion text once a course has begun. It builds up key information on five topics: binary operations, groups, quotient groups, isomorphisms and homomorphisms, and rings. It provides numerous examples, tables and diagrams, and its explanations are informed by research in mathematics education. The book also provides study advice focused on the skills that students need in order to learn successfully in their own Abstract Algebra courses. It explains how to interact productively with axioms, definitions, theorems and proofs, and how research in psychology should inform our beliefs about effective learning.

2-Dimensional Categories

2-Dimensional Categories

Category theory emerged in the 1940s in the work of Samuel Eilenberg and Saunders Mac Lane. It describes relationships between mathematical structures. Outside of pure mathematics, category theory is an important tool in physics, computer science, linguistics, and a quickly-growing list of other sciences. This book is about 2-dimensional categories, which add an extra dimension of richness and complexity to category theory. 2-Dimensional Categories is an introduction to 2-categories and bicategories, assuming only the most elementary aspects of category theory. A review of basic category theory is followed by a systematic discussion of 2-/bicategories, pasting diagrams, lax functors, 2-/bilimits, the Duskin nerve, 2-nerve, internal adjunctions, monads in bicategories, 2-monads, biequivalences, the Bicategorical Yoneda Lemma, and the Coherence Theorem for bicategories. Grothendieck fibrations and the Grothendieck construction are discussed next, followed by tricategories, monoidal bicategories, the Gray tensor product, and double categories. Completely detailed proofs of several fundamental but hard-to-find results are presented for the first time. With exercises and plenty of motivation and explanation, this book is useful for both beginners and experts.

2-Dimensional Categories

2-Dimensional Categories

Category theory emerged in the 1940s in the work of Samuel Eilenberg and Saunders Mac Lane. It describes relationships between mathematical structures. Outside of pure mathematics, category theory is an important tool in physics, computer science, linguistics, and a quickly-growing list of other sciences. This book is about 2-dimensional categories, which add an extra dimension of richness and complexity to category theory. 2-Dimensional Categories is an introduction to 2-categories and bicategories, assuming only the most elementary aspects of category theory. A review of basic category theory is followed by a systematic discussion of 2-/bicategories, pasting diagrams, lax functors, 2-/bilimits, the Duskin nerve, 2-nerve, internal adjunctions, monads in bicategories, 2-monads, biequivalences, the Bicategorical Yoneda Lemma, and the Coherence Theorem for bicategories. Grothendieck fibrations and the Grothendieck construction are discussed next, followed by tricategories, monoidal bicategories, the Gray tensor product, and double categories. Completely detailed proofs of several fundamental but hard-to-find results are presented for the first time. With exercises and plenty of motivation and explanation, this book is useful for both beginners and experts.

Modular Theory in Operator Algebras

Modular Theory in Operator Algebras

Author: Serban Valentin Stratila Format: Hardback Release Date: 31/12/2020

The first edition of this book appeared in 1981 as a direct continuation of Lectures of von Neumann Algebras (by S.V. Stratila and L. Zsido) and, until 2003, was the only comprehensive monograph on the subject. Addressing the students of mathematics and physics and researchers interested in operator algebras, noncommutative geometry and free probability, this revised edition covers the fundamentals and latest developments in the field of operator algebras. It discusses the group-measure space construction, Krieger factors, infinite tensor products of factors of type I (ITPFI factors) and construction of the type III_1 hyperfinite factor. It also studies the techniques necessary for continuous and discrete decomposition, duality theory for noncommutative groups, discrete decomposition of Connes, and Ocneanu's result on the actions of amenable groups. It contains a detailed consideration of groups of automorphisms and their spectral theory, and the theory of crossed products.

Taiwan's Politics In Action: Struggling To Win At The Ballot Box

Taiwan's Politics In Action: Struggling To Win At The Ballot Box

Author: John F (Rhodes College, Usa) Copper Format: Hardback Release Date: 13/12/2020

Taiwan's Politics in Action: Struggling to Win at the Ballot Box is about the most interesting and exciting aspects of Taiwan's politics: political competition in the form of electioneering, campaigns and voting. The author first analyzes the theories, constructs or simply ideas about elections, especially who wins them and why.The most discussed by the pundits and the scholars are the watermelon and the pendulum theory: voting as before or not. The economic, or pocketbook, theory is also popular - although whether this means economic growth or greater equity has changed. Which party or candidate has the most money is also predictive. Other constructs or simply ideas are also commonplace. Divide and conquer is another approach. Another is the best campaign agenda; so too picking the most attractive candidates. Professionalism in campaigning and the use of social media are also favorite ideas. So is the appeal to voters' ethnicity, espousing liberal or conservative ideas, using protest, focusing on constant concerns such as peace and corruption and finally, the appeals of populism and progressivism.The author then examines Taiwan's two most recent elections, the 2018 mid-term (or collection of local elections) and the 2020 national presidential and legislative election to apply the theories. The Nationalist Party or Kuomintang (KMT) won the former; the Democratic Progressive Party (DPP) won the latter, giving the observer a choice of evidence about how to win.The author concludes that Taiwan's democracy is being challenged, but is still popular in spite of strong external forces and other worries.

Analytical Chemistry of Foods

Analytical Chemistry of Foods

Author: Sujata Nagnath Mustapure Format: Hardback Release Date: 30/11/2020

Food chemistry is considered as a core subject in the area of food Science and food technology. It is the study of food composition, treatment processes and food interactions (including non-biological and biological). Analytical Chemistry of foods is a science which deals with attaining, treating and sharing data about structure and composition of matter. Food quality and safety are also investigated using the analytical techniques. Food Analytical techniques mainly encompass the specific and fundamental characteristics of optimization, development and validation stages of food analysis. This book consists of eight chapters. The first three chapters of the book comprises introductory text which introduces the readers with fundamentals of food chemistry, food constituents and food analysis. While last 5 chapters of the book focus on the description of key food constituents such as water, proteins, enzymes, carbohydrates and lipids. Readers from a diverse background can use this book for getting information on food chemistry. Moreover, this book can be used as a ready reference for students, researchers, teachers and scientists from the background of food chemistry.