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An Introduction to R and Python for Data Analysis A Side-By-Side Approach

An Introduction to R and Python for Data Analysis A Side-By-Side Approach

An Introduction to R and Python for Data Analysis helps teach students to code in both R and Python simultaneously. As both R and Python can be used in similar manners it is useful and efficient to learn both at the same time helping lecturers and students to teach and learn more save time whilst reinforcing the shared concepts and differences of the systems. This tandem learning is highly useful for students helping them to become literate in both languages and develop skills which will be handy after their studies. This book presumes no prior experience with computing and is intended to be used by students from a variety of backgrounds. The side-by-side formatting of this book helps introductory graduate students quickly grasp the basics of R and Python with the exercises providing helping them to teach themselves the skills they will need upon the completion of their course as employers now ask for competency in both R and Python. Teachers and lecturers will also find this book useful in their teaching providing a singular work to help ensure their students are well trained in both computer languages. All data for exercises can be found here: https://github. com/tbrown122387/r_and_python_book/tree/master/data. Instructors can access the solutions manual via the book's website. Key features: - Teaches R and Python in a side-by-side way. - Examples are tailored to aspiring data scientists and statisticians not software engineers. - Designed for introductory graduate students. Does not assume any mathematical background. | An Introduction to R and Python for Data Analysis A Side-By-Side Approach

GBP 74.99
1

Exploratory Multivariate Analysis by Example Using R

Exploratory Multivariate Analysis by Example Using R

Full of real-world case studies and practical advice Exploratory Multivariate Analysis by Example Using R Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical and hierarchical cluster analysis. The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework they present the principles indicators and ways of representing and visualising objects that are common to the exploratory methods. The authors show how to use categorical variables in a PCA context in which variables are quantitative how to handle more than two categorical variables in a CA context in which there are originally two variables and how to add quantitative variables in an MCA context in which variables are categorical. They also illustrate the methods using examples from various fields with related R code accessible in the FactoMineR package developed by the authors.

GBP 46.99
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A Criminologist's Guide to R Crime by the Numbers

A Criminologist's Guide to R Crime by the Numbers

A Criminologist's Guide to R: Crime by the Numbers introduces the programming language R and covers the necessary skills to conduct quantitative research in criminology. By the end of this book a person without any prior programming experience can take raw crime data be able to clean it visualize the data present it using R Markdown and change it to a format ready for analysis. A Criminologist's Guide to R focuses on skills specifically for criminology such as spatial joins mapping and scraping data from PDFs however any social scientist looking for an introduction to R for data analysis will find this useful. Key Features: Introduction to RStudio including how to change user preference settings. Basic data exploration and cleaning – subsetting loading data regular expressions aggregating data. Graphing with ggplot2. How to make maps (hotspot maps choropleth maps interactive maps). Webscraping and PDF scraping. Project management – how to prepare for a project how to decide which projects to do best ways to collaborate with people how to store your code (using git) and how to test your code. | A Criminologist's Guide to R Crime by the Numbers

GBP 74.99
1

Unity in Embedded System Design and Robotics A Step-by-Step Guide

Unity in Embedded System Design and Robotics A Step-by-Step Guide

The first book of its kind Unity in Embedded System Design and Robotics provides a step-by-step guide to Unity for embedded system design and robotics. It is an open gateway for anyone who wants to learn Unity through real projects and examples as well as a particularly useful aid for both professionals and students in the fields of embedded system design and robotics. Each chapter contains a unique project. The user is guided through the different windows and sections of Unity every step of the way. The book also includes projects that connect Unity to Arduino and Raspberry Pi which will help readers better understand various Unity applications in the real world. | Unity in Embedded System Design and Robotics A Step-by-Step Guide

GBP 82.99
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Learning Advanced Python by Studying Open Source Projects

Learning Advanced Python by Studying Open Source Projects

This book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial hell. It is a distillation of just one common Python user’s learning experience. The experience is packaged with exceptional teaching techniques careful dependence unraveling and most importantly passion. Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual this book mixes the technical knowledge real-world applications and more theoretical content providing readers with a practical and engaging approach to learning Python. Throughout this book readers will learn how to write Python code that is efficient readable and maintainable covering key topics such as data structures algorithms object-oriented programming and more. The author’s passion for Python shines through in this book making it an enjoyable and inspiring read for both beginners and experienced programmers.

GBP 44.99
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AI by Design A Plan for Living with Artificial Intelligence

AI by Design A Plan for Living with Artificial Intelligence

This book introduces the reader to Artificial Intelligence and its importance to our future. Campbell uses behavioural psychology explores technology economics real-life and historical examples to predict five future scenarios with AI. Illustrating through speculative fiction she describes possible futures after AI exceeds human capabilities. We are at a tipping point in history and must plan to ensure a successful co-existence with artificial intelligence. This book explains how to design for a future with AI so that rather than herald our downfall it helps us achieve a new renaissance. | AI by Design A Plan for Living with Artificial Intelligence

GBP 24.99
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Structural Equation Modeling Using R/SAS A Step-by-Step Approach with Real Data Analysis

Structural Equation Modeling Using R/SAS A Step-by-Step Approach with Real Data Analysis

There has been considerable attention to making the methodologies of structural equation modeling available to researchers practitioners and students along with commonly used software. Structural Equation Modelling Using R/SAS aims to bring it all together to provide a concise point-of-reference for the most commonly used structural equation modeling from the fundamental level to the advanced level. This book is intended to contribute to the rapid development in structural equation modeling and its applications to real-world data. Straightforward explanations of the statistical theory and models related to structural equation models are provided using a compilation of a variety of publicly available data to provide an illustration of data analytics in a step-by-step fashion using commonly used statistical software of R and SAS. This book is appropriate for anyone who is interested in learning and practicing structural equation modeling especially in using R and SAS. It is useful for applied statisticians data scientists and practitioners applied statistical analysts and scientists in public health and academic researchers and graduate students in statistics whilst also being of use to R&D professionals/practitioners in industry and governmental agencies. Key Features: Extensive compilation of commonly used structural equation models and methods from fundamental to advanced levels Straightforward explanations of the theory related to the structural equation models Compilation of a variety of publicly available data Step-by-step illustrations of data analysis using commonly used statistical software R and SAS Data and computer programs are available for readers to replicate and implement the new methods to better understand the book contents and for future applications Handbook for applied statisticians and practitioners | Structural Equation Modeling Using R/SAS A Step-by-Step Approach with Real Data Analysis

GBP 89.99
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Dynamic Web Programming and HTML5

Dynamic Web Programming and HTML5

With organizations and individuals increasingly dependent on the Web the need for competent well-trained Web developers and maintainers is growing. Helping readers master Web development Dynamic Web Programming and HTML5 covers specific Web programming languages APIs and coding techniques and provides an in-depth understanding of the underlying concepts theory and principles. The author leads readers through page structuring page layout/styling user input processing dynamic user interfaces database-driven websites and mobile website development. After an overview of the Web and Internet the book focuses on the new HTML5 and its associated open Web platform standards. It covers the HTML5 markup language and DOM new elements for structuring Web documents and forms CSS3 and important JavaScript APIs associated with HTML5. Moving on to dynamic page generation and server-side programming with PHP the text discusses page templates form processing session control user login database access and server-side HTTP requests. It also explores more advanced topics such as XML and PHP/MySQL. Suitable for a one- or two-semester course at the advanced undergraduate or beginning graduate level this comprehensive and up-to-date guide helps readers learn modern Web technologies and their practical applications. Numerous examples illustrate how the programming techniques and other elements work together to achieve practical goals. Online ResourceEncouraging hands-on practice the book‘s companion website at http://dwp. sofpower. com helps readers gain experience with the technologies and techniques involved in building good sites. Maintained by the author the site offers: Live examples organized by chapter and cross-referenced in the text Programs from the text bundled in a downloadable code package Searchable index and appendices Ample resource l

GBP 180.00
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Monitoring the Health of Populations by Tracking Disease Outbreaks Saving Humanity from the Next Plague

Monitoring the Health of Populations by Tracking Disease Outbreaks Saving Humanity from the Next Plague

With COVID-19 sweeping across the globe with near impunity it is thwarting governments and health organizations efforts to contain it. Not since the 1918 Spanish Flu have citizens of developed countries experienced such a large-scale disease outbreak that is having devastating health and economic impacts. One reason such outbreaks are not more common has been the success of the public health community including epidemiologists and biostatisticians in identifying and then mitigating or eliminating the outbreaks. Monitoring the Health of Populations by Tracking Disease Outbreaks: Saving Humanity from the Next Plague is the story of the application of statistics for disease detection and tracking. The work of public health officials often crucially depends on statistical methods to help discern whether an outbreak may be occurring and if there is sufficient evidence of an outbreak then to locate and track it. Statisticians also help collect critical information and they analyze the resulting data to help investigators zero in on a cause for a disease. With the recent outbreaks of diseases such as swine and bird flu Ebola and now COVID-19 the role that epidemiologists and biostatisticians play is more important than ever. Features: · Discusses the crucial roles of statistics in early disease detection. · Outlines the concepts and methods of disease surveillance. · Covers surveillance techniques for communicable diseases like Zika and chronic diseases such as cancer. · Gives real world examples of disease investigations including smallpox syphilis anthrax yellow fever and microcephaly (and its relationship to the Zika virus). Via the process of identifying an outbreak finding its cause and developing a plan to prevent its reoccurrence this book tells the story of how medical and public health professionals use statistics to help mitigate the effects of disease. This book will help readers understand how statisticians and epidemiologists help combat the spread of such diseases in order to improve public health across the world. | Monitoring the Health of Populations by Tracking Disease Outbreaks Saving Humanity from the Next Plague

GBP 31.99
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Security for Software Engineers

Security for Software Engineers

Security for Software Engineers is designed to introduce security concepts to undergraduate software engineering students. The book is divided into four units each targeting activities that a software engineer will likely be involved in within industry. The book explores the key areas of attack vectors code hardening privacy and social engineering. Each topic is explored from a theoretical and a practical-application standpoint. Features:Targets software engineering students - one of the only security texts to target this audience. Focuses on the white-hat side of the security equation rather than the black-hat side. Includes many practical and real-world examples that easily translate into the workplace. Covers a one-semester undergraduate course. Describes all aspects of computer security as it pertains to the job of a software engineer and presents problems similar to that which an engineer will encounter in the industry. This text will equip students to make knowledgeable security decisions be productive members of a security review team and write code that protects a user’s information assets.

GBP 39.99
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Finite Automata

Finite Automata

Interest in finite automata theory continues to grow not only because of its applications in computer science but also because of more recent applications in mathematics particularly group theory and symbolic dynamics. The subject itself lies on the boundaries of mathematics and computer science and with a balanced approach that does justice to both aspects this book provides a well-motivated introduction to the mathematical theory of finite automata. The first half of Finite Automata focuses on the computer science side of the theory and culminates in Kleene's Theorem which the author proves in a variety of ways to suit both computer scientists and mathematicians. In the second half the focus shifts to the mathematical side of the theory and constructing an algebraic approach to languages. Here the author proves two main results: Schützenberger's Theorem on star-free languages and the variety theorem of Eilenberg and Schützenberger. Accessible even to students with only a basic knowledge of discrete mathematics this treatment develops the underlying algebra gently but rigorously and nearly 200 exercises reinforce the concepts. Whether your students' interests lie in computer science or mathematics the well organized and flexible presentation of Finite Automata provides a route to understanding that you can tailor to their particular tastes and abilities.

GBP 59.99
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Bayesian Networks With Examples in R

Bayesian Networks With Examples in R

Bayesian Networks: With Examples in R Second Edition introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples illustrate each step of the modelling process and discuss side by side the underlying theory and its application using R code. The examples start from the simplest notions and gradually increase in complexity. In particular this new edition contains significant new material on topics from modern machine-learning practice: dynamic networks networks with heterogeneous variables and model validation. The first three chapters explain the whole process of Bayesian network modelling from structure learning to parameter learning to inference. These chapters cover discrete Gaussian and conditional Gaussian Bayesian networks. The following two chapters delve into dynamic networks (to model temporal data) and into networks including arbitrary random variables (using Stan). The book then gives a concise but rigorous treatment of the fundamentals of Bayesian networks and offers an introduction to causal Bayesian networks. It also presents an overview of R packages and other software implementing Bayesian networks. The final chapter evaluates two real-world examples: a landmark causal protein-signalling network published in Science and a probabilistic graphical model for predicting the composition of different body parts. Covering theoretical and practical aspects of Bayesian networks this book provides you with an introductory overview of the field. It gives you a clear practical understanding of the key points behind this modelling approach and at the same time it makes you familiar with the most relevant packages used to implement real-world analyses in R. The examples covered in the book span several application fields data-driven models and expert systems probabilistic and causal perspectives thus giving you a starting point to work in a variety of scenarios. Online supplementary materials include the data sets and the code used in the book which will all be made available from https://www. bnlearn. com/book-crc-2ed/ | Bayesian Networks With Examples in R

GBP 82.99
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How Things Work The Computer Science Edition

How Things Work The Computer Science Edition

It’s axiomatic to state that people fear what they do not understand and this is especially true when it comes to technology. However despite their prevalence computers remain shrouded in mystery and many users feel apprehensive when interacting with them. Smartphones have only exacerbated the issue. Indeed most users of these devices leverage only a small fraction of the power they hold in their hands. How Things Work: The Computer Science Edition is a roadmap for readers who want to overcome their technophobia and harness the full power of everyday technology. Beginning with the basics the book demystifies the mysterious world of computer science explains its fundamental concepts in simple terms and answers the questions many users feel too intimidated to ask. By the end of the book readers will understand how computers and smart devices function and more important how they can make these devices work for them. To complete the picture the book also introduces readers to the darker side of modern technology: security and privacy concerns identity theft and threats from the Dark Web. | How Things Work The Computer Science Edition

GBP 48.99
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Design of Experiments for Generalized Linear Models

Design of Experiments for Generalized Linear Models

Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM little information is available on how to collect the data that are to be analysed in this way. This is the first book focusing specifically on the design of experiments for GLMs. Much of the research literature on this topic is at a high mathematical level and without any information on computation. This book explains the motivation behind various techniques reduces the difficulty of the mathematics or moves it to one side if it cannot be avoided and gives examples of how to write and run computer programs using R. FeaturesThe generalisation of the linear model to GLMsBackground mathematics and the use of constrained optimisation in RCoverage of the theory behind the optimality of a designIndividual chapters on designs for data that have Binomial or Poisson distributionsBayesian experimental designAn online resource contains R programs used in the bookThis book is aimed at readers who have done elementary differentiation and understand minimal matrix algebra and have familiarity with R. It equips professional statisticians to read the research literature. Nonstatisticians will be able to design their own experiments by following the examples and using the programs provided. | Design of Experiments for Generalized Linear Models

GBP 38.99
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Differential Equations Theory Technique and Practice

Differential Equations Theory Technique and Practice

Differential equations is one of the oldest subjects in modern mathematics. It was not long after Newton and Leibniz invented the calculus that Bernoulli and Euler and others began to consider the heat equation and the wave equation of mathematical physics. Newton himself solved differential equations both in the study of planetary motion and also in his consideration of optics. Today differential equations is the centerpiece of much of engineering of physics of significant parts of the life sciences and in many areas of mathematical modeling. This text describes classical ideas and provides an entree to the newer ones. The author pays careful attention to advanced topics like the Laplace transform Sturm–Liouville theory and boundary value problems (on the traditional side) but also pays due homage to nonlinear theory to modeling and to computing (on the modern side). This book began as a modernization of George Simmons’ classic Differential Equations with Applications and Historical Notes. Prof. Simmons invited the author to update his book. Now in the third edition this text has become the author’s own and a unique blend of the traditional and the modern. The text describes classical ideas and provides an entree to newer ones. Modeling brings the subject to life and makes the ideas real. Differential equations can model real life questions and computer calculations and graphics can then provide real life answers. The symbiosis of the synthetic and the calculational provides a rich experience for students and prepares them for more concrete applied work in future courses. Additional Features Anatomy of an Application sections. Historical notes continue to be a unique feature of this text. Math Nuggets are brief perspectives on mathematical lives or other features of the discipline that will enhance the reading experience. Problems for Review and Discovery give students some open-ended material for exploration and further learning. They are an important means of extending the reach of the text and for anticipating future work. This new edition is re-organized to make it more useful and more accessible. The most frequently taught topics are now up front. And the major applications are isolated in their own chapters. This makes this edition the most useable and flexible of any previous editions. | Differential Equations Theory Technique and Practice

GBP 82.99
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Real World AI Ethics for Data Scientists Practical Case Studies

Real World AI Ethics for Data Scientists Practical Case Studies

In the midst of the fourth industrial revolution big data is weighed in gold placing enormous power in the hands of data scientists – the modern AI alchemists. But great power comes with greater responsibility. This book seeks to shape in a practical diverse and inclusive way the ethical compass of those entrusted with big data. Being practical this book provides seven real-world case studies dealing with big data abuse. These cases span a range of topics from the statistical manipulation of research in the Cornell food lab through the Facebook user data abuse done by Cambridge Analytica to the abuse of farm animals by AI in a chapter co-authored by renowned philosophers Peter Singer and Yip Fai Tse. Diverse and inclusive given the global nature of this revolution this book provides case-by-case commentary on the cases by scholars representing non-Western ethical approaches (Buddhist Jewish Indigenous and African) as well as Western approaches (consequentialism deontology and virtue). We hope this book will be a lighthouse for those debating ethical dilemmas in this challenging and ever-evolving field. | Real World AI Ethics for Data Scientists Practical Case Studies

GBP 42.99
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Method of Averaging for Differential Equations on an Infinite Interval Theory and Applications

Method of Averaging for Differential Equations on an Infinite Interval Theory and Applications

In recent years mathematicians have detailed simpler proofs of known theorems have identified new applications of the method of averaging and have obtained many new results of these applications. Encompassing these novel aspects Method of Averaging of the Infinite Interval: Theory and Applications rigorously explains the modern theory of the method of averaging and provides a solid understanding of the results obtained when applying this theory. The book starts with the less complicated theory of averaging linear differential equations (LDEs) focusing on almost periodic functions. It describes stability theory and Shtokalo's method and examines various applications including parametric resonance and the construction of asymptotics. After establishing this foundation the author goes on to explore nonlinear equations. He studies standard form systems in which the right-hand side of a system is proportional to a small parameter and proves theorems similar to Banfi's theorem. The final chapters are devoted to systems with a rapidly rotating phase. Covering an important asymptotic method of differential equations this book provides a thorough understanding of the method of averaging theory and its resulting applications. | Method of Averaging for Differential Equations on an Infinite Interval Theory and Applications

GBP 210.00
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Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications

Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications

This book describes in a basic way the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems. The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed mathematical models become more and more accurate by including a greater volume of data but this requires the solution of larger and harder algebraic systems. In recent years research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers. | Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications

GBP 150.00
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Flexible Imputation of Missing Data Second Edition

Flexible Imputation of Missing Data Second Edition

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes like deletion or mean imputation only work under highly restrictive conditions which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data. | Flexible Imputation of Missing Data Second Edition

GBP 38.99
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The Essentials of Data Science: Knowledge Discovery Using R

The Essentials of Data Science: Knowledge Discovery Using R

The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data. Building on over thirty years’ experience in teaching and practising data science the author encourages a programming-by-example approach to ensure students and practitioners attune to the practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets. The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.

GBP 145.00
1

Measuring Society

Measuring Society

Collecting and analyzing data on unemployment inflation and inequality help describe the complex world around us. When published by the government such data are called official statistics. They are reported by the media used by politicians to lend weight to their arguments and by economic commentators to opine about the state of society. Despite such widescale use explanations about how these measures are constructed are seldom provided for a non-technical reader. This Measuring Society book is a short accessible guide to six topics: jobs house prices inequality prices for goods and services poverty and deprivation. Each relates to concepts we use on a personal level to form an understanding of the society in which we live: We need a job a place to live and food to eat. Using data from the United States we answer three basic questions: why how and for whom these statistics have been constructed. We add some context and flavor by discussing the historical background. This book provides the reader with a good grasp of these measures. Chaitra H. Nagaraja is an Associate Professor of Statistics at the Gabelli School of Business at Fordham University in New York. Her research interests include house price indices and inequality measurement. Prior to Fordham Dr. Nagaraja was a researcher at the U. S. Census Bureau. While there she worked on projects relating to the American Community Survey.

GBP 24.99
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Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project

Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project

This book is about building platforms for pandemic prediction. It provides an overview of probabilistic prediction for pandemic modeling based on a data-driven approach. It also provides guidance on building platforms with currently available technology using tools such as R Shiny and interactive plotting programs. The focus is on the integration of statistics and computing tools rather than on an in-depth analysis of all possibilities on each side. Readers can follow different reading paths through the book depending on their needs. The book is meant as a basis for further investigation of statistical modelling implementation tools monitoring aspects and software functionalities. Features: A general but parsimonious class of models to perform statistical prediction for epidemics using a Bayesian approach Implementation of automated routines to obtain daily prediction results How to interactively visualize the model results Strategies for monitoring the performance of the predictions and identifying potential issues in the results Discusses the many decisions required to develop and publish online platforms Supplemented by an R package and its specific functionalities to model epidemic outbreaks The book is geared towards practitioners with an interest in the development and presentation of results in an online platform of statistical analysis of epidemiological data. The primary audience includes applied statisticians biostatisticians computer scientists epidemiologists and professionals interested in learning more about epidemic modelling in general including the COVID-19 pandemic and platform building. The authors are professors at the Statistics Department at Universidade Federal de Minas Gerais. Their research records exhibit contributions applied to a number of areas of Science including Epidemiology. Their research activities include books published with Chapman and Hall/CRC and papers in high quality journals. They have also been involved with academic management of graduate programs in Statistics and one of them is currently the President of the Brazilian Statistical Association. | Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project

GBP 56.99
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