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Introduction to Sociology
This book provides an invaluable introduction to his historical and conceptual engagement with sociology.
R 2,705.00
Introduction to Generalized Linear Models
An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection, and a Postface on good statistical practice.Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before focusing on methods for analyzing particular kinds of data. It covers Normal, Poisson, and Binomial distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian models, and Markov chain Monte Carlo (MCMC) methods. Introduces GLMs in a way that enables readers to understand the unifying structure that underpins them Discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, non-linear associations and longitudinal analysis Connects Bayesian analysis and MCMC methods to fit GLMs Contains numerous examples from business, medicine, engineering, and the social sciences Provides the example code for R, Stata, and WinBUGS to encourage implementation of the methods Offers the data sets and solutions to the exercises online Describes the components of good statistical practice to improve scientific validity and reproducibility of results.Using popular statistical software programs, this concise and accessible text illustrates practical approaches to estimation, model fitting, and model comparisons.
R 3,448.32
Introduction to Computational Systems Biology
This book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networks—a fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. Key Features: A hands-on approach to modelling Covers a broad spectrum of modelling, from static networks to dynamic models and constraint-based models Thoughtful exercises to test and enable understanding of concepts State-of-the-art chapters on exciting new developments, like community modelling and biological circuit design Emphasis on coding and software tools for systems biology Companion website featuring lecture videos, figure slides, codes, supplementary exercises, further reading, and appendices: https://ramanlab.github.io/SysBioBook/An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks is highly multi-disciplinary and will appeal to biologists, engineers, computer scientists, mathematicians and others.
R 2,810.54
Introduction to Credit Risk
Introduction to Credit Risk focuses on analysis of credit risk, derivatives, equity investments, portfolio management, quantitative methods, and risk management. In terms of application, this book can be used as an important tool to explain how to generate data rows of expected exposure to counterparty credit risk. The book also directs the reader on how to visualize, in real time, the results of this data, generated with a Java tool.Features Uses an in-depth case study to illustrate multiple factors in counterparty credit risk exposures Suitable for quantitative risk managers at banks, as well as students of finance, financial mathematics, and software engineering Provides the reader with numerous examples and applicationsGiulio Carlone has an MBA, a PhD, and a Master’s degree in Computer Science from the University of Italy. He is a member of the software system engineering staff of the Department of Computer Science at University College London. He has 20 years of practical experience in technical software engineering and quantitative finance engineering in the commercial sector. His research interests include the use of communication strategies and the implementation of plans and projects using financial software for requirement specifications, requirements analysis, and architectural design.
R 11,221.90
R 4,160.00
Interactive Introduction to Mathematical Analysis
This book provides a rigorous course in the calculus of functions of a real variable. Its gentle approach, particularly in its early chapters, makes it especially suitable for students who are not headed for graduate school but, for those who are, this book also provides the opportunity to engage in a penetrating study of real analysis. The companion on-screen version of this text contains hundreds of links to alternative approaches, more complete explanations and solutions to exercises; links that make it more friendly than any printed book could be. In addition, there are links to a wealth of optional material that an instructor can select for a more advanced course, and that students can use as a reference long after their first course has ended. The on-screen version also provides exercises that can be worked interactively with the help of the computer algebra systems that are bundled with Scientific Notebook.
R 2,562.72
Introduction to Syntax
This comprehensive textbook is an engaging introduction to syntax. Clearly organized and accessible, it provides students with a thorough grounding in the analysis of syntactic structure using data from a typologically wide variety of languages. The book guides students through the basic concepts involved in syntactic analysis and goes on to prepare them for further work in any syntactic theory, using examples from a range of phenomena in human languages. It also includes a chapter on theories of syntax. Each chapter includes generous exercises and recommendations for further study. The emphasis on languages and data sets this book apart from other introductions to syntax. This book is an essential text for undergraduate and graduate students on courses devoted to the study of syntax. It will also be very valuable to students in other cognitive science fields who are interested in language.
R 6,169.09
Introduction to Probability and Statistics Using Basic
This volume introduces the theoretical ideas in probability and statistics by means of examples. The strengths of the BASIC computer language are exploited to illustrate probabilistic and statistical ideas. Topics described by the Committee on the Under-graduate Program in Mathematics are included.
R 15,906.09
R 618.00
Gentle Introduction to Scientific Computing
Scientific Computation has established itself as a stand-alone area of knowledge at the borderline between computer science and applied mathematics. Nonetheless, its interdisciplinary character cannot be denied: its methodologies are increasingly used in a wide variety of branches of science and engineering.A Gentle Introduction to Scientific Computing intends to serve a very broad audience of college students across a variety of disciplines. It aims to expose its readers to some of the basic tools and techniques used in computational science, with a view to helping them understand what happens "behind the scenes" when simple tools such as solving equations, plotting and interpolation are used.To make the book as practical as possible, the authors explore their subject both from a theoretical, mathematical perspective and from an implementation-driven, programming perspective.FeaturesMiddle-ground approach between theory and implementation.Suitable reading for a broad range of students in STEM disciplines. Could be used as the primary text for a first course in scientific computing.Introduces mathematics majors, without any prior computer science exposure, to numerical methods.All mathematical knowledge needed beyond Calculus (together with the most widely used Calculus notation and concepts) is introduced in the text to make it self-contained. The erratum document for A Gentle Introduction to Scientific Computing can be accessed here.
R 5,642.28
Introduction to Quantum Field Theory with Applications to Quantum Gravity
Applications of quantum field theoretical methods to gravitational physics, both in the semiclassical and the full quantum frameworks, require a careful formulation of the fundamental basis of quantum theory, with special attention to such important issues as renormalization, quantum theory of gauge theories, and especially effective action formalism. The first part of this graduate textbook provides both a conceptual and technical introduction to the theory ofquantum fields. The presentation is consistent, starting from elements of group theory, classical fields, and moving on to the effective action formalism in general gauge theories. Compared to other existing books, the general formalism of renormalization in described in more detail, and special attentionpaid to gauge theories. This part can serve as a textbook for a one-semester introductory course in quantum field theory. In the second part, we discuss basic aspects of quantum field theory in curved space, and perturbative quantum gravity. More than half of Part II is written with a full exposition of details, and includes elaborated examples of simplest calculations. All chapters include exercises ranging from very simple ones to those requiring small original investigations. The selection of material of the second part is done using the “must-know” principle. This means we included detailedexpositions of relatively simple techniques and calculations, expecting that the interested reader will be able to learn more advanced issues independently after working through the basic material, and completing the exercises.
R 4,061.00
Introduction to Dynamics
A thorough and logically fluent textbook on elementary dynamics, primarily intended for first-year Mathematics undergraduates. A basic knowledge of calculus and elementary statics is required, though no previous knowledge of dynamics is assumed. Pars, a former lecturer in Mathematics at Cambridge, also provides an introductory grounding in ideas that will recur throughout the book, such as vectors and the fundamentals of Newtonian mechanics. Included in the text are a number of worked examples to illustrate the application of the theory to concrete problems, and exercises for practice at the ends of the chapters.
R 2,625.68
R 1,129.02
Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel and R
The second edition of Introduction to Biostatistical Applications in Health Research delivers a thorough examination of the basic techniques and most commonly used statistical methods in health research. Retaining much of what was popular with the well-received first edition, the thoroughly revised second edition includes a new chapter on testing assumptions and how to evaluate whether those assumptions are satisfied and what to do if they are not. The newest edition contains brand-new code examples for using the popular computer language R to perform the statistical analyses described in the chapters within. You'll learn how to use Excel to generate datasets for R, which can then be used to conduct statistical calculations on your data. The book also includes a companion website with a new version of BAHR add-in programs for Excel. This new version contains new programs for nonparametric analyses, Student-Newman-Keuls tests, and stratified analyses. Readers will also benefit from coverage of topics like: Extensive discussions of basic and foundational concepts in statistical methods, including Bayes' Theorem, populations, and samplesA treatment of univariable analysis, covering topics like continuous dependent variables and ordinal dependent variablesAn examination of bivariable analysis, including regression analysis and correlation analysisAn analysis of multivariate calculations in statistics and how testing assumptions, like assuming Gaussian distributions or equal variances, affect statistical outcomes Perfect for health researchers of all kinds, Introduction to Biostatistical Applications in Health Research also belongs on the bookshelves of anyone who wishes to better understand health research literature. Even those without a great deal of mathematical background will benefit greatly from this text.
R 5,017.00
Introduction to Correspondence Analysis
Master the fundamentals of correspondence analysis with this illuminating resource An Introduction to Correspondence Analysis assists researchers in improving their familiarity with the concepts, terminology, and application of several variants of correspondence analysis. The accomplished academics and authors deliver a comprehensive and insightful treatment of the fundamentals of correspondence analysis, including the statistical and visual aspects of the subject. Written in three parts, the book begins by offering readers a description of two variants of correspondence analysis that can be applied to two-way contingency tables for nominal categories of variables. Part Two shifts the discussion to categories of ordinal variables and demonstrates how the ordered structure of these variables can be incorporated into a correspondence analysis. Part Three describes the analysis of multiple nominal categorical variables, including both multiple correspondence analysis and multi-way correspondence analysis. Readers will benefit from explanations of a wide variety of specific topics, for example: Simple correspondence analysis, including how to reduce multidimensional space, measuring symmetric associations with the Pearson Ratio, constructing low-dimensional displays, and detecting statistically significant pointsNon-symmetrical correspondence analysis, including quantifying asymmetric associationsSimple ordinal correspondence analysis, including how to decompose the Pearson Residual for ordinal variablesMultiple correspondence analysis, including crisp coding and the indicator matrix, the Burt Matrix, and stackingMulti-way correspondence analysis, including symmetric multi-way analysis Perfect for researchers who seek to improve their understanding of key concepts in the graphical analysis of categorical data, An Introduction to Correspondence Analysis will also assist readers already familiar with correspondence analysis who wish to review the theoretical and foundational underpinnings of crucial concepts.
R 2,246.00
Introduction to Statistical Physics
Written by a world-renowned theoretical physicist, Introduction to Statistical Physics, Second Edition clarifies the properties of matter collectively in terms of the physical laws governing atomic motion. This second edition expands upon the original to include many additional exercises and more pedagogically oriented discussions that fully explain the concepts and applications.The book first covers the classical ensembles of statistical mechanics and stochastic processes, including Brownian motion, probability theory, and the Fokker–Planck and Langevin equations. To illustrate the use of statistical methods beyond the theory of matter, the author discusses entropy in information theory, Brownian motion in the stock market, and the Monte Carlo method in computer simulations. The next several chapters emphasize the difference between quantum mechanics and classical mechanics—the quantum phase. Applications covered include Fermi statistics and semiconductors and Bose statistics and Bose–Einstein condensation. The book concludes with advanced topics, focusing on the Ginsburg–Landau theory of the order parameter and the special kind of quantum order found in superfluidity and superconductivity.Assuming some background knowledge of classical and quantum physics, this textbook thoroughly familiarizes advanced undergraduate students with the different aspects of statistical physics. This updated edition continues to provide the tools needed to understand and work with random processes.
R 4,465.02
Introduction to Queueing Systems
Queueing is an aspect of modern life that we encounter at every step in our daily activities. Whether it happens at the checkout counter in the supermarket or in accessing the Internet, the basic phenomenon of queueing arises whenever a shared facility needs to be accessed for service by a ]arge number of jobs or customers. The study of queueing is important as it gravides both a theoretical background to the kind of service that we may expect from such a facility and the way in which the facility itself may be designed to provide some specified grade of service to its customers. Our study of queueing was basically motivated by its use in the study of communication systems and computer networks. The various computers, routers and switches in such a network may be modelled as individual queues. The whole system may itself be modelled as a queueing network providing the required service to the messages, packets or cells that need to be carried. Application of queueing theory provides the theoretical framework for the design and study of such networks. The purpose of this book is to support a course on queueing systems at the senior undergraduate or graduate Ievels. Such a course would then provide the theoretical background on which a subsequent course on the performance modeHing and analysis of computer networks may be based.
R 4,655.15
Introduction To Quantum Statistical Mechanics (2nd Edition)
Introduction to Quantum Statistical Mechanics (Second Edition) may be used as an advanced textbook by graduate students, even ambitious undergraduates in physics. It is also suitable for non experts in physics who wish to have an overview of some of the classic and fundamental quantum models in the subject. The explanation in the book is detailed enough to capture the interest of the reader, and complete enough to provide the necessary background material needed to dwell further into the subject and explore the research literature.
R 2,615.58
Introduction to the Sociology of Ignorance
Ignorance is typically thought of as the absence or opposite of knowledge. In global societies that equate knowledge with power, ignorance is seen as a liability that can and should be overcome through increased education and access to information. In recent years, scholars from the social sciences, natural sciences and humanities have challenged this assumption, and have explored the ways in which ignorance can serve as a vital resource – perhaps the most vital resource – in social and political life. In this seminal volume, leading theorists of ignorance from anthropology, sociology and legal studies explore the productive role of ignorance in maintaining and destabilizing political regimes, entrenching corporate power, and shaping policy developments in climate science, global health, and global economic governance. From debates over death tolls during the war in Iraq, to the root causes of the global financial crisis, to poverty reduction strategies at the World Bank, contributors shed light on the unexpected ways that ignorance is actively harnessed by both the powerful and the marginalized in order to achieve different objectives. This eye-opening volume suggests that to understand power today, we must enrich our understanding of ignorance. This book was originally published as a special issue of Economy and Society.
R 8,572.00
Introduction to Sociolinguistics
This is an introduction to key themes and topics in contemporary sociolinguistics, focussing particularly on identity. This is a definitive introductory text to modern sociolinguistics that looks at the study of language and society through the concept of identity. It uses these sociolinguistic constructs of identity to tie together current concepts and methods in the field, offering a full overview of the discipline, both past and present. Deckert and Vickers adopt an interdisciplinary approach, introducing work from a variety of fields that examine sociolinguistic data, from linguistics to anthropology, sociology, psychology and education. The book moves from looking at language varieties and globalization to a close examination of language in social interaction, covering the concepts of ideology and power. Throughout, the authors offer keen insight into all of the topics, issues and methods that students of language and society will need to understand. The chapters contain a range of pedagogical features, including key terms, study questions, chapter summaries and further reading.This is an essential new text for all those studying contemporary sociolinguistics, suitable for undergraduates and postgraduates alike.
R 6,768.00
Introduction to Statistical Modelling
This book is about generalized linear models as described by NeIder and Wedderburn (1972). This approach provides a unified theoretical and computational framework for the most commonly used statistical methods: regression, analysis of variance and covariance, logistic regression, log-linear models for contingency tables and several more specialized techniques. More advanced expositions of the subject are given by McCullagh and NeIder (1983) and Andersen (1980). The emphasis is on the use of statistical models to investigate substantive questions rather than to produce mathematical descriptions of the data. Therefore parameter estimation and hypothesis testing are stressed. I have assumed that the reader is familiar with the most commonly used statistical concepts and methods and has some basic knowledge of calculus and matrix algebra. Short numerical examples are used to illustrate the main points. In writing this book I have been helped greatly by the comments and criticism of my students and colleagues, especially Anne Young. However, the choice of material, and the obscurities and errors are my responsibility and I apologize to the reader for any irritation caused by them. For typing the manuscript under difficult conditions I am grateful to Anne McKim, Jan Garnsey, Cath Claydon and Julie Latimer.
R 1,529.62
Introduction to System Reliability Theory
This textbook provides the tools for a modern post-graduate introductory course on system reliability theory. It focuses on probabilistic aspects of the theory, including recent results based on signatures, stochastic orders, aging classes, copulas and distortion (or aggregation) functions. The reader requires on an introductory knowledge on probability theory and mathematics. The book serves both for graduate students in mathematics and for engineering students in various disciplines as well as students learning survival analysis, network reliability or simple game theory. Included also are brief introductions to the basic aspects of lifetime modelling, stochastic comparisons, aging classes, mixtures and copula theory. The book develops this knowledge with worked examples and supplies code for the program R so that students can explore its lessons and techniques.
R 2,284.79
Easy Statistics for Food Science with R
Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data.
R 3,531.00
Introduction to Statistical Modeling of Extreme Values
Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.
R 5,450.31
R 4,417.00
Informal Introduction To Stochastic Calculus With Applications, An
The goal of this book is to present Stochastic Calculus at an introductory level and not at its maximum mathematical detail. The author aims to capture as much as possible the spirit of elementary deterministic Calculus, at which students have been already exposed. This assumes a presentation that mimics similar properties of deterministic Calculus, which facilitates understanding of more complicated topics of Stochastic Calculus.
R 1,721.14
Introduction to Statistics
The introductory statistics course presents serious pedagogical problems to the instructor. For the great majority of students, the course represents the only formal contact with statistical thinking that he or she will have in college. Students come from many different fields of study, and a large number suffer from math anxiety. Thus, an instructor who is willing to settle for some limited objectives will have a much better chance of success than an instructor who aims for a broad exposure to statistics. Many statisticians agree that the primary objective of the introductory statistics course is to introduce students to variability and uncertainty and how to cope with them when drawing inferences from observed data. Addi tionally, the introductory COurse should enable students to handle a limited number of useful statistical techniques. The present text, which is the successor to the author's Introduction to Statistics: A Nonparametric Approach (Houghton Mifflin Company, Boston, 1976), tries to meet these objectives by introducing the student to the ba sic ideas of estimation and hypothesis testing early in the course after a rather brief introduction to data organization and some simple ideas about probability. Estimation and hypothesis testing are discussed in terms of the two-sample problem, which is both conceptually simpler and more realistic than the one-sample problem that customarily serves as the basis for the discussion of statistical inference.
R 1,577.39
Introduction to Data Technologies
Providing key information on how to work with research data, Introduction to Data Technologies presents ideas and techniques for performing critical, behind-the-scenes tasks that take up so much time and effort yet typically receive little attention in formal education. With a focus on computational tools, the book shows readers how to improve their awareness of what tasks can be achieved and describes the correct approach to perform these tasks. Practical examples demonstrate the most important pointsThe author first discusses how to write computer code using HTML as a concrete example. He then covers a variety of data storage topics, including different file formats, XML, and the structure and design issues of relational databases. After illustrating how to extract data from a relational database using SQL, the book presents tools and techniques for searching, sorting, tabulating, and manipulating data. It also introduces some very basic programming concepts as well as the R language for statistical computing. Each of these topics has supporting chapters that offer reference material on HTML, CSS, XML, DTD, SQL, R, and regular expressions.One-stop shop of introductory computing information Written by a member of the R Development Core Team, this resource shows readers how to apply data technologies to tasks within a research setting. Collecting material otherwise scattered across many books and the web, it explores how to publish information via the web, how to access information stored in different formats, and how to write small programs to automate simple, repetitive tasks.
R 4,483.86
Concise Introduction to Cultural Anthropology
This book offers a concise and accessible overview of cultural anthropology for those coming to the subject for the first time. It introduces key areas of the discipline and touches on its historical developments and applied aspects. As well as traditional topics such as social organization, politics, and economics, the book engages with important contemporary issues including race, gender, sexuality, and colonialism.In a beginner-friendly format, this book is ideal for students of anthropology, as well as for the interested reader as an introduction to the subject.
R 1,042.07
Introduction to Numerical Analysis
Numerical analysis is an increasingly important link between pure mathematics and its application in science and technology. This textbook provides an introduction to the justification and development of constructive methods that provide sufficiently accurate approximations to the solution of numerical problems, and the analysis of the influence that errors in data, finite-precision calculations, and approximation formulas have on results, problem formulation and the choice of method. It also serves as an introduction to scientific programming in MATLAB, including many simple and difficult, theoretical and computational exercises. A unique feature of this book is the consequent development of interval analysis as a tool for rigorous computation and computer assisted proofs, along with the traditional material.
R 4,108.57
Introduction to Population Ecology
Introduction to Population Ecology, 2nd Edition is a comprehensive textbook covering all aspects of population ecology. It uses a wide variety of field and laboratory examples, botanical to zoological, from the tropics to the tundra, to illustrate the fundamental laws of population ecology. Controversies in population ecology are brought fully up to date in this edition, with many brand new and revised examples and data. Each chapter provides an overview of how population theory has developed, followed by descriptions of laboratory and field studies that have been inspired by the theory. Topics explored include single-species population growth and self-limitation, life histories, metapopulations and a wide range of interspecific interactions including competition, mutualism, parasite-host, predator-prey and plant-herbivore. An additional final chapter, new for the second edition, considers multi-trophic and other complex interactions among species. Throughout the book, the mathematics involved is explained with a step-by-step approach, and graphs and other visual aids are used to present a clear illustration of how the models work. Such features make this an accessible introduction to population ecology; essential reading for undergraduate and graduate students taking courses in population ecology, applied ecology, conservation ecology, and conservation biology, including those with little mathematical experience.
R 3,000.00
Informal Introduction To Stochastic Calculus With Applications, An
Most branches of science involving random fluctuations can be approached by Stochastic Calculus. These include, but are not limited to, signal processing, noise filtering, stochastic control, optimal stopping, electrical circuits, financial markets, molecular chemistry, population dynamics, etc. All these applications assume a strong mathematical background, which in general takes a long time to develop. Stochastic Calculus is not an easy to grasp theory, and in general, requires acquaintance with the probability, analysis and measure theory.The goal of this book is to present Stochastic Calculus at an introductory level and not at its maximum mathematical detail. The author's goal was to capture as much as possible the spirit of elementary deterministic Calculus, at which students have been already exposed. This assumes a presentation that mimics similar properties of deterministic Calculus, which facilitates understanding of more complicated topics of Stochastic Calculus.The second edition contains several new features that improved the first edition both qualitatively and quantitatively. First, two more chapters have been added, Chapter 12 and Chapter 13, dealing with applications of stochastic processes in Electrochemistry and global optimization methods.This edition contains also a final chapter material containing fully solved review problems and provides solutions, or at least valuable hints, to all proposed problems. The present edition contains a total of about 250 exercises.This edition has also improved presentation from the first edition in several chapters, including new material.
R 2,858.00
Introduction to the Art of Programming Using Scala
With its flexibility for programming both small and large projects, Scala is an ideal language for teaching beginning programming. Yet there are no textbooks on Scala currently available for the CS1/CS2 levels. Introduction to the Art of Programming Using Scala presents many concepts from CS1 and CS2 using a modern, JVM-based language that works well for both programming in the small and programming in the large. The book progresses from true programming in the small to more significant projects later, leveraging the full benefits of object orientation. It first focuses on fundamental problem solving and programming in the small using the REPL and scripting environments. It covers basic logic and problem decomposition and explains how to use GUIs and graphics in programs. The text then illustrates the benefits of object-oriented design and presents a large collection of basic data structures showing different implementations of key ADTs along with more atypical data structures. It also introduces multithreading and networking to provide further motivating examples. By using Scala as the language for both CS1 and CS2 topics, this textbook gives students an easy entry into programming small projects as well as a firm foundation for taking on larger-scale projects. Many student and instructor resources are available at www.programmingusingscala.net
R 4,249.00
Introduction to Evaluation
Both practical and theoretical in approach, this book is the perfect companion for student researchers and policy makers alike. It provides actionable advice for planning and implementing evaluations, while also instilling an ability to assess the evaluations of others and consider the ways in which evaluation evidence could influence policy and practice.Drawing upon a wide range of examples from policy areas like education, criminal justice, and health and social care, this book showcases how evaluation is an interdisciplinary research practice with a spectrum of applications. Each chapter contains philosophical underpinnings and applied knowledge as well as examples from published evaluations. Specific topics include how to:Choose an approach to evaluationPlan, design, and conduct evaluationsApproach evaluations using theories of changeDifferentiate between process, impact, and economic evaluationsUnderstand the role of quantitative and qualitative methods in data collection Use systematic reviews and other tools to assess and disseminate evaluation findingsFrom getting started in the field to turning evidence into policy, this book will guide you through every step of the evaluation process.
R 3,056.54
Introduction to People Analytics
How can HR practitioners with little or no experience of analytics feel confident in their ability to find, analyse and use workforce data to make better business decisions? This book has the answers.An understanding of people analytics is a crucial skill for all HR professionals. This new edition provides expert guidance on the key aspects of analytics, enabling all HR professionals to feel confident in their ability to handle employee and organizational data. It features new material on applying data to respond to external disruption such as COVID-19 as well as how to develop a people analytics journey. There is also advice on recruiting people analytics specialists and embedding new data-driven operating models within HR.This book is essential reading for all HR professionals to develop understanding of how and where HR analytics can make a tangible difference to organizations. With updated case studies and thought leadership examples from companies including NHS, AstraZeneca and Swarovski, this book demonstrates how people analytics can be leveraged to improve culture and employee engagement, increase performance and reduce costs.
R 4,533.00
Introduction to Probability and Random Variables
This textbook provides a straightforward, clear explanation of probability and random variables for communications engineering students. The author focuses on the most essential subjects of probability and random variables, eliminating unnecessary details of this difficult subject. After an introduction to the topic, the author covers the essentials of experiments, sample spaces, events, and probability laws, while investigating how they relate to communications engineering work. He goes on to discuss total probability theorems, after which he covers discrete random variables and continuous random variables. The author uses his years of teaching probability and random variable concepts to engineering students to form the text in a very understandable manner. The book features exercises, examples, case studies, and other key classroom materials
R 2,489.99
Introduction to Bayesian Analysis
This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing.Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques.Many topics are at the cutting edge of statistical research. Solutions to common inference problems appear throughout the text along with discussion of what prior to choose. There is a discussion of elicitation of a subjective prior as well as the motivation, applicability, and limitations of objective priors. By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrinsic Bayes Factors, which the authors have successfully applied to geological mapping.The style is informal but clear. Asymptotics is used to supplement simulation or understand some aspects of the posterior.
R 3,049.23
Introduction to Statistical Signal Processing
This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.
R 6,046.57
Introduction to Multivariate Analysis
This book provides an introduction to the analysis of multivariate data. It should be suitable for statisticians and other research workers who are familiar with basic probability theory and elementary inference, and also have a basic grounding in matrix algebra. The book should also be suitable as a text for undergraduate and postgraduate statistics courses on multivariate analysis. The book covers a wider range oftopics than some other books in this area. It deals with preliminary data analysis, principal component and factor analysis and traditional normal-theory material. It also covers cluster analysis and scaling techniques. In writing the book, we have tried to provide a reasonable blend of theory and practice, in contrast to much of the existing literature which concentrates on one or other aspect. Enough theory is given to introduce the concepts and to make the topics mathematically interesting. But we also discuss the use (and misuse) of the techniques in practice and present appropriate real-life examples. Although the book is primarily an introductory text, we have nevertheless added appropriate references for further reading, so that the reader may extend his studies if he wishes.
R 3,300.85
Introduction to Queueing Systems with Telecommunication Applications
The book is the extended and revised version of the 1st edition and is composed of two main parts: mathematical background and queueing systems with applications. The mathematical background is a self-containing introduction to the stochastic processes of the later studied queueing systems. It starts with a quick introduction to probability theory and stochastic processes and continues with chapters on Markov chains and regenerative processes. More recent advances of queueing systems are based on phase type distributions, Markov arrival processes and quasy birth death processes, which are introduced in the last chapter of the first part.The second part is devoted to queueing models and their applications. After the introduction of the basic Markovian (from M/M/1 to M/M/1//N) and non-Markovian (M/G/1, G/M/1) queueing systems, a chapter presents the analysis of queues with phase type distributions, Markov arrival processes (from PH/M/1 to MAP/PH/1/K). The next chapter presents the classical queueing network results and the rest of this part is devoted to the application examples. There are queueing models for bandwidth charing with different traffic classes, slotted multiplexers, media access protocols like Aloha and IEEE 802.11b, priority systems and retrial systems.An appendix supplements the technical content with Laplace and z transformation rules, Bessel functions and a list of notations. The book contains examples and exercises throughout and could be used for graduate students in engineering, mathematics and sciences.Reviews of first edition:"The organization of the book is such that queueing models are viewed as special cases of more general stochastic processes, such as birth-death or semi-Markov processes. … this book is a valuable addition to the queuing literature and provides instructors with a viable alternative for a textbook to be used in a one- or two-semester course on queueing models, at the upper undergraduate or beginning graduate levels."Charles Knessl, SIAM Review, Vol. 56 (1), March, 2014
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