Data Structures Using C

C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to use data structures and algorithms plus the first comprehensive reference for C# implementation of data structures and algorithms found in the .NET Framework library, as well as those developed by the programmer. The approach is very practical, using timing tests rather than Big O notation to analyze the efficiency of an approach. Coverage includes arrays and array lists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as probabilistic algorithms and dynamic programming. This is the perfect resource for C# professionals and students alike.

C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to use data structures and algorithms plus the first comprehensive reference for C# implementation of data structures and algorithms found in the .NET Framework library, as well as those developed by the programmer. The approach is very practical, using timing tests rather than Big O notation to analyze the efficiency of an approach. Coverage includes arrays and array lists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as probabilistic algorithms and dynamic programming. This is the perfect resource for C# professionals and students alike.

This is the first Visual Basic.NET book to provide a comprehensive discussion of the major data structures and algorithms. Here, instead of having to translate material on C++ or Java, the professional or student VB.NET programmer will find a tutorial on how to use data structures and algorithms and a reference for implementation using VB.NET for data structures and algorithms from the .NET Framework Class Library as well as those which must be developed by the programmer. In an object-oriented fashion, the author presents arrays and arraylists, linked lists, hash tables, dictionaries, trees, graphs, sorting and searching as well as more advanced algorithms, such as probabilistic algorithms and dynamic programming. His approach is very practical, for example using timing tests rather than Big O analysis to compare the performance of data structures and algorithms. This book can be used in both beginning and advanced computer programming courses that use the VB.NET language and, most im

This text closely examines ideas, analysis, and implementation details of data structures as a specialised topic in applied algorithms. It looks at efficient ways to realise query and update operations on sets of numbers, intervals, or strings by various data structures, including: search trees; structures for sets of intervals or piece-wise constant functions; orthogonal range search structures; heaps; union-find structures; dynamization and persistence of structures; structures for strings; and hash tables. Instead of relegating data structures to trivial material used to illustrate object-oriented programming methodology, this is the first volume to show data structures as a crucial algorithmic topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.

This text closely examines ideas, analysis, and implementation details of data structures as a specialised topic in applied algorithms. It looks at efficient ways to realise query and update operations on sets of numbers, intervals, or strings by various data structures, including: search trees; structures for sets of intervals or piece-wise constant functions; orthogonal range search structures; heaps; union-find structures; dynamization and persistence of structures; structures for strings; and hash tables. Instead of relegating data structures to trivial material used to illustrate object-oriented programming methodology, this is the first volume to show data structures as a crucial algorithmic topic. Numerous code examples in C and more than 500 references make Advanced Data Structures an indispensable text.

Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques so that programmers can develop their own functional data structures. It includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs can easily be adapted to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

Most books on data structures assume an imperative language like C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques so that programmers can develop their own functional data structures. It includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs can easily be adapted to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

Plant remains can preserve a critical part of history of life on Earth. While telling the fascinating evolutionary story of plants and vegetation across the last 500 million years, this book also crucially offers non-specialists a practical guide to studying, dealing with and interpreting plant fossils. It shows how various techniques can be used to reveal the secrets of plant fossils and how to identify common types, such as compressions and impressions. Incorporating the concepts of evolutionary floras, this second edition includes revised data on all main plant groups, the latest approaches to naming plant fossils using fossil-taxa and techniques such as tomography. With extensive illustrations of plant fossils and living plants, the book encourages readers to think of fossils as once-living organisms. It is written for students on introductory or intermediate courses in palaeobotany, palaeontology, plant evolutionary biology and plant science, and for amateurs interested in studyin

Valuation and Risk Management in Energy Markets surveys the mechanics of energy markets and the valuation of structures commonly arising in practice. The presentation balances quantitative issues and practicalities facing portfolio managers, with substantial attention paid to the ways in which common methods fail in practice and to alternative methods when they exist. The material spans basic fundamentals of markets, statistical analysis of price dynamics, and a sequence of increasingly challenging structures, concluding with issues arising at the enterprise level. In totality, the material has been selected to provide readers with the analytical foundation required to function in modern energy trading and risk management groups.

Until recently, dominant theoretical paradigms in the comparative social sciences did not highlight states as organizational structures or as potentially autonomous actors. Indeed, the term 'state' was rarely used. Current work, however, increasingly views the state as an agent which, although influenced by the society that surrounds it, also shapes social and political processes. The contributors to this volume, which includes some of the best recent interdisciplinary scholarship on states in relation to social structures, make use of theoretically engaged comparative and historical investigations to provide improved conceptualizations of states and how they operate. Each of the book's major parts presents a related set of analytical issues about modern states, which are explored in the context of a wide range of times and places, both contemporary and historical, and in developing and advanced-industrial nations. The first part examines state strategies in newly developing countries.

Presenting a global and interdisciplinary approach to plant ecology, this much-awaited new edition of the book Plants and Vegetation integrates classical themes with the latest ideas, models, and data. Keddy draws on extensive teaching experience to bring the field to life, guiding students through essential concepts with numerous real-world examples and full-colour illustrations throughout. The chapters begin by presenting the wider picture of the origin of plants and their impact on the Earth, before exploring the search for global patterns in plants and vegetation. Chapters on resources, stress, competition, herbivory, and mutualism explore causation, and a concluding chapter on conservation addresses the concern that one-third of all plant species are at risk of extinction. The scope of this edition is broadened further by a new chapter on population ecology, along with extensive examples including South African deserts, the Guyana Highlands of South America, Himalayan forests and

This concise yet comprehensive textbook examines political, social, and cultural developments in the Soviet Union and the post-Soviet period. It begins by identifying the social tensions and political inconsistencies that spurred radical change in Russia's government, from the turn of the century to the revolution of 1917. Peter Kenez presents this revolution as a crisis of authority that the creation of the Soviet Union resolved. The text traces the progress of the Soviet Union through the 1920s, the years of the New Economic Policies, and into the Stalinist order. It illustrates how post-Stalin Soviet leaders struggled to find ways to rule the country without using Stalin's methods - but also without openly repudiating the past - and to negotiate a peaceful but antipathetic coexistence with the capitalist West. This updated third edition includes substantial new material, discussing the challenges Russia currently faces in the era of Putin.

Public perceptions of political ethics are at the heart of current political debate. Drawing on original data, this book is the first general account of popular understandings of political ethics in contemporary British politics. It offers new insights into how citizens understand political ethics and integrity and how they form judgments of their leaders. By locating these insights against the backdrop of contemporary British political ethics, the book shows how current institutional preoccupations with standards of conduct all too often miss the mark. While the use of official resources is the primary focus of much regulation, politicians' consistency, frankness and sincerity, which citizens tend to see in terms of right and wrong, are treated as 'normal politics'. The authors suggest that new approaches may need to be adopted if public confidence in politicians' integrity is to be restored.

Scientists have a choice concerning what role they should play in political debates and policy formation, particularly in terms of how they present their research. This book is about understanding this choice, what considerations are important to think about when deciding, and the consequences of such choices for the individual scientist and the broader scientific enterprise. Rather than prescribing what course of action each scientist ought to take, the book aims to identify a range of options for individual scientists to consider in making their own judgments about how they would like to position themselves in relation to policy and politics. Using examples from a range of scientific controversies and thought-provoking analogies from other walks of life, The Honest Broker challenges us all - scientists, politicians and citizens - to think carefully about how best science can contribute to policy-making and a healthy democracy.

This volume brings together original essays by scholars working on a diverse range of empirical issues, but whose work is in each case informed by a 'historical institutional' approach to the study of politics. By bringing these pieces together, the volume highlights the methodological and theoretical foundations of this approach and illustrates the general contributions it has made to comparative politics. The essays demonstrate the potential of the approach to illuminate a broad range of issues such as how and why institutions change, how political ideas are filtered through institutional structures in the formation of specific policies, and how institutional structure can have unintended effects on the shaping of policy. The reader is provided with both a thorough understanding of the method of analysis and an overview of the theoretical underpinnings of the approach.

Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions wil

Data structures are the fundamental building blocks of any computer program, used for storing, representing and manipulating data in a computer. This text presents the basic concepts of data structures as part of the art of writing computer programs. The author concentrates on the fundamentals of what should be done to solve a problem efficiently rather than technical implementation details. The text includes pseudocode and covers all the most common data structures, such as queues, stacks, trees, heaps, and hash tables, along with the basics of searching, sorting, and coding. This book can supplement any undergraduate algorithms or discrete math course and will also be accessible to students and researchers in other quantitative disciplines. No prerequisites beyond introductory programming and basic mathematics are required, and the accessible, conceptual presentation will appeal to undergraduates in many quantitative fields. Carefully designed problem sets with selected solutions wil

Compact data structures help represent data in reduced space while allowing it to be queried, navigated, and operated in compressed form. They are essential tools for efficiently handling massive amounts of data by exploiting the memory hierarchy. They also reduce the resources needed in distributed deployments and make better use of the limited memory in low-end devices. The field has developed rapidly, reaching a level of maturity that allows practitioners and researchers in application areas to benefit from the use of compact data structures. This first comprehensive book on the topic focuses on the structures that are most relevant for practical use. Readers will learn how the structures work, how to choose the right ones for their application scenario, and how to implement them. Researchers and students in the area will find in the book a definitive guide to the state of the art in compact data structures.

Fundamentals of OOP and Data Structures in Java is a text for an introductory course on classical data structures. Part One of the book presents the basic principles of Object-Oriented Programming (OOP) and Graphical User Interface (GUI) programming with Java as the example language. Part Two introduces each of the major data structures with supporting, GUI-based laboratory programs designed to reinforce the basic concepts and principles of the text. These laboratories allow the reader to explore and experiment with the properties of each data structure. All source code for the laboratories is available on the web. By integrating the principles of OOP and GUI programming, this book takes the unique path of presenting the fundamental issues of data structures within the context of paradigms that are essential to today's professional software developer. The authors assume the reader has only an elementary understanding of Java and no experience with OOP.

本書是一部系統性探討海洋與沿岸波浪的專業著作，兼顧物理意義與統計分析，適合研究所學生、研究人員與工程實務者閱讀。內容從觀測技術談起，介紹現地量測與遙測方法，並逐步建立描述波浪的參數與統計架構。書中詳述線性波理論在外海與近岸水域的應用，說明波浪在不同水深與地形條件下的行為差異，並深入介紹 SWAN 波浪模式，協助讀者理解現代數值模擬在工程與研究中的角色。全書結構嚴謹、插圖清楚，是理解風生波浪與海岸波動不可或缺的參考書。Waves in Oceanic and Coastal Waters describes the observation, analysis and prediction of wind-generated waves in the open ocean, in shelf seas, and in coastal regions with islands, channels, tidal flats and inlets, estuaries, fjords and lagoons. Most of this richly illustrated book is devoted to the physical aspects of waves. After introducing observation techniques for waves, both at sea and from space, the book defines the parameters that characterise waves. Using basic statistical and physical concepts, the author discusses the prediction of waves in oceanic and coastal waters, first in terms of generalised observations, and then in terms of the more theoretical framework of the spectral energy balance. He gives the results of established theories and also the direction in wh

Things which we regard as the everyday objects of consumption (and hence re-purchase), and essential to any decent, civilised lifestyle, have not always been so: in former times, everyday objects would have passed from one generation to another, without anyone dreaming of acquiring new ones. How, therefore, have people in the modern world become 'prisoners of objects', as Rousseau put it? The celebrated French cultural historian Daniel Roche answers this fundamental question using insights from economics, politics, demography and geography, as well as his own extensive historical knowledge. Professor Roche places familiar objects and commodities - houses, clothes, water - in their wider historical and anthropological contexts, and explores the origins of some of the daily furnishings of modern life. A History of Everyday Things is a pioneering essay that sheds light on the origins of the consumer society and its social and political repercussions, and thereby the birth of the modern w

This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.

This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are pro

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

Chunyan Li is a course instructor with many years of experience in teaching about time series analysis. His book is essential for students and researchers in oceanography and other subjects in the Earth sciences, looking for a complete coverage of the theory and practice of time series data analysis using MATLAB. This textbook covers the topic's core theory in depth, and provides numerous instructional examples, many drawn directly from the author's own teaching experience, using data files, examples, and exercises. The book explores many concepts, including time; distance on Earth; wind, current, and wave data formats; finding a subset of ship-based data along planned or random transects; error propagation; Taylor series expansion for error estimates; the least squares method; base functions and linear independence of base functions; tidal harmonic analysis; Fourier series and the generalized Fourier transform; filtering techniques: sampling theorems: finite sampling effects; wavelet

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

SAS programming is a creative and iterative process designed to empower you to make the most of your organization's data. This friendly guide provides you with a repertoire of essential SAS tools for data management, whether you are a new or an infrequent user. Most useful to students and programmers with little or no SAS experience, it takes a no-frills, hands-on tutorial approach to getting started with the software. You will find immediate guidance in navigating, exploring, visualizing, cleaning, formatting, and reporting on data using SAS and JMP. Step-by-step demonstrations, screenshots, handy tips, and practical exercises with solutions equip you to explore, interpret, process and summarize data independently, efficiently and effectively.

SAS programming is a creative and iterative process designed to empower you to make the most of your organization's data. This friendly guide provides you with a repertoire of essential SAS tools for data management, whether you are a new or an infrequent user. Most useful to students and programmers with little or no SAS experience, it takes a no-frills, hands-on tutorial approach to getting started with the software. You will find immediate guidance in navigating, exploring, visualizing, cleaning, formatting, and reporting on data using SAS and JMP. Step-by-step demonstrations, screenshots, handy tips, and practical exercises with solutions equip you to explore, interpret, process and summarize data independently, efficiently and effectively.

Fatigue Design of Marine Structures provides students and professionals with a theoretical and practical background for fatigue design of marine structures including sailing ships, offshore structures for oil and gas production, and other welded structures subject to dynamic loading such as wind turbine structures. Industry expert Inge Lotsberg brings more than forty years of experience in design and standards-setting to this comprehensive guide to the basics of fatigue design of welded structures. Topics covered include laboratory testing, S-N data, different materials, different environments, stress concentrations, residual stresses, acceptance criteria, non-destructive testing, improvement methods, probability of failure, bolted connections, grouted connections, and fracture mechanics. Featuring twenty chapters, three hundred diagrams, forty-seven example calculations, and resources for further study, Fatigue Design of Marine Structures is intended as the complete reference work for

Storytelling is a fundamental mode of everyday interaction. This book is based upon the Narrative Corpus (NC), a specialized corpus of naturally occurring narratives, and provides new paths for its study. Christoph Rühlemann uses the NC's narrative-specific annotation and XPath and XQuery, query languages that allow the retrieval of complex data structures, to facilitate large-scale quantitative investigations into how narrators and recipients collaborate in storytelling. Empirical analyses are validated using R, a programming language and environment for statistical computing and graphics. Using this unique data and methodological base, Rühlemann reveals new insights, including the discovery of turntaking patterns specific to narrative, the first investigation of textual colligation in spoken data, the unearthing of how speech reports, as discourse units, form striking patterns at utterance level, and the identification of the story climax as the sequential context in which recipient

Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.

Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.

LEDA is a library of efficient data types and algorithms and a platform for combinatorial and geometric computing on which application programs can be built. In each of the core computer science areas of data structures, graph and network algorithms, and computational geometry, LEDA covers all (and more) that is found in the standard textbooks. LEDA is the first such library; it is written in C++ and is available on many types of machine. Whilst the software is freely available worldwide and is installed at hundreds of sites, this is the first book devoted to the library. Written by the main authors of LEDA, it is the definitive account, describing how the system is constructed and operates and how it can be used. The authors supply ample examples from a range of areas to show how the library can be used in practice, making the book essential for all workers in algorithms, data structures and computational geometry.

Michael McMillan provides a complete presentation of the object-oriented features of the Visual Basic .NET language for advanced Visual Basic programmers. Beginning with an introduction to abstract data types and their initial implementation using structures, he explains standard OOP topics including class design, inheritance, access modifiers and scoping issues, abstract classes, design and implemention of interfaces and design patterns, and refactoring in VB.NET. More advanced OOP topics are included as well, such as reflection, object persistence, and serialization. To tie everything together, McMillan demonstrates sound OOP design and implementation principles through practical examples of standard Windows applications, database applications using ADO.NET, Web-based applications using ASP.NET, and Windows service applications.

Computer simulations provide a powerful tool for understanding ecological and evolutionary systems. Simulating Ecological and Evolutionary Systems in C models a diverse range of biological processes and systems, including competition, foraging, predation, mating systems, and life-history optimization, by simulating large collections of interacting individuals. Using the widely available computer programming language C, the book starts with elementary programs modeling stochastic birth-death processes, slowly increasing programming complexity as the chapters progress. All the important features of C are covered, including arrays, files, pointers, and structures, within biologically motivated simulations. Although computer simulations of extremely complicated biological processes are released from rigid mathematical constraints, each of the simulations is also placed in the context of a mathematical formulation examined either analytically or numerically. Procedures covered include testi

As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.