{"title":"Series: Statistics in Practice","description":"\u003cp\u003e\u003cstrong\u003eStatistics in Practice\u003c\/strong\u003e offers readers a diverse exploration of data applied across a wide range of disciplines, from finance and business to health and technology. This series bridges theory and real-world applications, providing insights that deepen understanding of complex concepts through practical examples and analytical thinking.\u003c\/p\u003e\n\n\u003cp\u003eWhether you are interested in the latest methods in computing, philosophical perspectives on decision-making, or the statistical underpinnings of markets and wellness, this collection presents carefully crafted works that illuminate the role of statistics in everyday and specialised contexts.\u003c\/p\u003e","products":[{"product_id":"multiple-imputation-and-its-application-by-angela-m-wood-9781119756088","title":"Multiple Imputation and its Application","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003e\u003cem\u003eMultiple Imputation and its Application\u003c\/em\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eThe most up-to-date edition of a bestselling guide to analysing partially observed data\u003c\/strong\u003e\u003c\/p\u003e\n\n\u003cp\u003eIn this comprehensively revised Second Edition of \u003cem\u003eMultiple Imputation and its Application\u003c\/em\u003e, a team of distinguished statisticians delivers an overview of the issues raised by missing data, the rationale for multiple imputation as a solution, and the practicalities of applying it in a multitude of settings.\u003c\/p\u003e\n\n\u003cp\u003eWith an accessible and carefully structured presentation aimed at quantitative researchers, \u003cem\u003eMultiple Imputation and its Application\u003c\/em\u003e is illustrated with a range of examples and offers key mathematical details. The book includes a wide range of theoretical and computer-based exercises, tested in the classroom, which are especially useful for users of R or Stata. Readers will find:\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eA comprehensive overview of one of the most effective and popular methodologies for dealing with incomplete data sets\u003c\/li\u003e\n  \u003cli\u003eCareful discussion of key concepts\u003c\/li\u003e\n  \u003cli\u003eA range of examples illustrating the key ideas\u003c\/li\u003e\n  \u003cli\u003ePractical advice on using multiple imputation\u003c\/li\u003e\n  \u003cli\u003eExercises and examples designed for use in the classroom and\/or private study\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eWritten for applied researchers looking to use multiple imputation with confidence, and for methods researchers seeking an accessible overview of the topic, \u003cem\u003eMultiple Imputation and its Application\u003c\/em\u003e will also earn a place in the libraries of graduate students undertaking quantitative analyses.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":46854694895852,"sku":"9781119756088","price":159.99,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/8f9e338a6c51af8d60c22ae92e1b691b.jpg?v=1759266291"},{"product_id":"quantitative-finance-by-maria-cristina-mariani-9781118629956","title":"Quantitative Finance","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003e\u003cstrong\u003ePresents a multitude of topics relevant to the quantitative finance community by combining the best of the theory with the usefulness of applications.\u003c\/strong\u003e\u003c\/p\u003e\n\n\u003cp\u003eWritten by accomplished teachers and researchers in the field, this book presents quantitative finance theory through applications to specific practical problems and comes with accompanying coding techniques in R and MATLAB, as well as some generic pseudo-algorithms relevant to modern finance. It also offers over 300 examples and exercises that are appropriate for the beginning student as well as the practitioner in the field.\u003c\/p\u003e\n\n\u003cp\u003eThe \u003ci\u003eQuantitative Finance\u003c\/i\u003e book is divided into four parts. Part One begins by providing readers with the theoretical backdrop needed from probability and stochastic processes. Useful finance concepts used throughout the book are also presented.\u003c\/p\u003e\n\n\u003cp\u003eIn Part Two of the book, the classical Black-Scholes-Merton model is introduced in a uniquely accessible and understandable way. Implied volatility as well as local volatility surfaces are discussed. Solutions to Partial Differential Equations (PDE), wavelets, and Fourier transforms are presented. Several methodologies for pricing options, namely tree methods, finite difference method, and Monte Carlo simulation methods, are also discussed. This part concludes with a discussion on stochastic differential equations (SDEs).\u003c\/p\u003e\n\n\u003cp\u003eThe third part of this book delves into several new and advanced models from current literature, such as general Lévy processes, nonlinear PDEs for stochastic volatility models in a transaction fee market, PDEs in a jump-diffusion with stochastic volatility models, and factor and copulas models.\u003c\/p\u003e\n\n\u003cp\u003eIn Part Four, the book concludes with a solid presentation of the typical topics in fixed income securities and derivatives. Models for pricing bonds, marketable securities, credit default swaps (CDS), and securitizations are discussed.\u003c\/p\u003e\n\n\u003cul\u003e\n    \u003cli\u003eClassroom-tested over a three-year period with the input of students and experienced practitioners.\u003c\/li\u003e\n    \u003cli\u003eEmphasises the volatility of financial analyses and interpretations.\u003c\/li\u003e\n    \u003cli\u003eWeaves theory with application throughout the book.\u003c\/li\u003e\n    \u003cli\u003eUtilises R and MATLAB software programs.\u003c\/li\u003e\n    \u003cli\u003ePresents pseudo-algorithms for readers who do not have access to any particular programming system.\u003c\/li\u003e\n    \u003cli\u003eSupplemented with an extensive author-maintained website that includes helpful teaching hints, datasets, software programs, and additional content.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003e\u003ci\u003eQuantitative Finance\u003c\/i\u003e is an ideal textbook for upper-undergraduate and beginning graduate students in statistics, financial engineering, quantitative finance, and mathematical finance programmes. It will also appeal to practitioners in the same fields.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":47000717557996,"sku":"9781118629956","price":283.99,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/b11573d89d5aebe9b8f2d42c6be74fbd.jpg?v=1773004719"},{"product_id":"individual-participant-data-meta-analysis-9781119333722","title":"Individual Participant Data Meta-Analysis","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003e\u003ci\u003eIndividual Participant Data Meta-Analysis: A Handbook for Healthcare Research\u003c\/i\u003e provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points.\u003c\/p\u003e\n\n\u003cp\u003eSplit into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data.\u003c\/p\u003e\n\n\u003cp\u003eIntended for a broad audience, the book will enable the reader to:\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eUnderstand the advantages of the IPD approach and decide when it is needed over a conventional systematic review\u003c\/li\u003e\n  \u003cli\u003eRecognise the scope, resources and challenges of IPD meta-analysis projects\u003c\/li\u003e\n  \u003cli\u003eAppreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators\u003c\/li\u003e\n  \u003cli\u003eUnderstand how to obtain, check, manage and harmonise IPD from multiple studies\u003c\/li\u003e\n  \u003cli\u003eExamine risk of bias (quality) of IPD and minimise potential biases throughout the project\u003c\/li\u003e\n  \u003cli\u003eUnderstand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them\u003c\/li\u003e\n  \u003cli\u003eClearly report and disseminate IPD meta-analyses to inform policy, practice and future research\u003c\/li\u003e\n  \u003cli\u003eCritically appraise existing IPD meta-analysis projects\u003c\/li\u003e\n  \u003cli\u003eAddress specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eDetailed examples and case studies are provided throughout.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":47470863483116,"sku":"9781119333722","price":162.99,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/9781119333722-individual-participant-data-meta-analysis.jpg?v=1775229215"},{"product_id":"statistical-methods-for-hospital-monitoring-with-r-by-kerrie-l-mengersen-9781118596302","title":"Statistical Methods for Hospital Monitoring with R","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003eHospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals to analyse their often non-independent data, which is frequently in the form of trended, over-dispersed, and sometimes auto-correlated time series; this is often difficult to analyse using standard office software.\u003c\/p\u003e\n\n\u003cp\u003eIt provides much-needed guidance on data analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise.\u003c\/p\u003e\n\n\u003cp\u003eThe book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interest.\u003c\/p\u003e\n\n\u003cp\u003e\u003cem\u003eStatistical Methods for Hospital Monitoring with R\u003c\/em\u003e:\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eProvides functions to perform quality improvement and infection management data analysis.\u003c\/li\u003e\n  \u003cli\u003eExplores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events.\u003c\/li\u003e\n  \u003cli\u003eProvides a summary of key non-statistical aspects of hospital safety and easy-to-use functions.\u003c\/li\u003e\n  \u003cli\u003eOffers R scripts on an accompanying website enabling analyses to be performed by the reader: \u003ca href=\"http:\/\/www.wiley.com\/go\/hospital_monitoring\"\u003ehttp:\/\/www.wiley.com\/go\/hospital_monitoring\u003c\/a\u003e\n\u003c\/li\u003e\n  \u003cli\u003eCovers issues that will be of increasing importance in the future, such as generalised additive models, and complex systems, networks, and power laws.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":47471617081580,"sku":"9781118596302","price":157.99,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/9781118596302-statistical-methods-for-hospital-monitoring-with-r.jpg?v=1775247980"}],"url":"https:\/\/bookhero.pro\/collections\/series-statistics-in-practice.oembed","provider":"Book Hero","version":"1.0","type":"link"}