Probability and statistics Books
Cambridge University Press Comparison of Statistical Experiments 36 Encyclopedia of Mathematics and its Applications Series Number 36
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£79.10
Cambridge University Press TimeSeries Analysis A Comprehensive Introduction for Social Scientists
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£45.59
Cambridge University Press Structural Equation Modeling Applications in Ecological and Evolutionary Biology
Book SynopsisStructural equation modelling (SEM) is a technique that is used to estimate, analyse and test models that specify relationships among variables. The ability to conduct such analyses is essential for many problems in ecology and evolutionary biology. This book begins by explaining the theory behind the statistical methodology, including chapters on conceptual issues, the implementation of an SEM study and the history of the development of SEM. The second section provides examples of analyses on biological data including multi-group models, means models, P-technique and time-series. The final section of the book deals with computer applications and contrasts three popular SEM software packages. Aimed specifically at biological researchers and graduate students, this book will serve as valuable resource for both learning and teaching the SEM methodology. Moreover, data sets and programs that are presented in the book can also be downloaded from a website to assist the learning process.Table of ContentsPart I. Theory: 1. Structural equation modelling: an introduction Scott L. Hershberger, George A. Marcoulides and Makeba M. Parramore; 2. Concepts of structural equation modelling in biological research Bruce H. Pugesek; 3. Modelling a complex conceptual theory of population change in the Shiras moose: history and recasting as a structural equation model Bruce H. Pugesek; 4. A short history of structural equation models Adrian Tomer; 5. Guidelines for the implementation and publication of structural equation models Adrian Tomer and Bruce H. Pugesek; Part II. Applications: 6. Modelling intra-individual variability and change in bio-behavioural developmental processes Patricia H. Hawley and Todd D. Little; 7. Examining the relationship between environmental variables and ordination axes using latent variables and structural equation modelling James B. Grace; 8. From biological hypotheses to structural equation models: the imperfection of causal translation Bill Shipley; 9. Analysing dynamic systems: a comparison of structural equation modelling and system dynamics modelling Peter S. Hovmand; 10. Estimating analysis of variance models as structural equation models Michael J. Rovine and Peter C. M. Molenaar; 11. Comparing groups using structural equations James B. Grace; 12. Modelling means in latent variable models of natural selection Bruce H. Pugesek; 13. Modeling manifest variables in longitudinal designs - a two-stage approach Bret E. Fuller, Alexander von Eye; Philip K. Wood and Bobby D. Keeland; Part III. Computing: 14. A comparison of the SEM software packages Amos, EQS and LISREL Alexander von Eye and Bret E. Fuller; Index.
£48.44
Cambridge University Press Fixed Point Theory and Applications 141 Cambridge Tracts in Mathematics Series Number 141
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£42.74
Cambridge University Press Statistical Models
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£133.00
Cambridge University Press Asymptotic Efficiency of Nonparametric Tests
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£35.14
Cambridge University Press Statistical Calculation for Beginners
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£37.99
Cambridge University Press A Students Guide to Data and Error Analysis
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£66.50
Cambridge University Press Empirical Processes in MEstimation 06 Cambridge Series in Statistical and Probabilistic Mathematics Series Number 6
Book SynopsisThe theory of empirical processes provides valuable tools for the development of asymptotic theory in (nonparametric) statistical models, and makes possible the unified treatment of a number of them. This book reveals the relation between the asymptotic behaviour of M-estimators and the complexity of parameter space. Virtually all results are proved using only elementary ideas developed within the book; there is minimal recourse to abstract theoretical results. To make the results concrete, a detailed treatment is presented for two important examples of M-estimation, namely maximum likelihood and least squares. The theory also covers estimation methods using penalties and sieves. Many illustrative examples are given, including the Grenander estimator, estimation of functions of bounded variation, smoothing splines, partially linear models, mixture models and image analysis. Graduate students and professionals in statistics as well as those with an interest in applications, to such areaTrade Review'… well written and provides a modern contribution to a very important class of nonparametric estimators.' N. D. C. Veraverbeke, Publication of the International Statistical Institute'… this excellent book will be extremely useful for graduate students and researchers in the general area of nonparametric estimation. It is a welcome addition to the existing literature and certainly recommended.' Niew Archief voor WiskundeTable of ContentsPreface; Reading guide; 1. Introduction; 2. Notations and definitions; 3. Uniform laws of large numbers; 4. First applications: consistency; 5. Increments of empirical processes; 6. Central limit theorems; 7. Rates of convergence for maximum likelihood estimators; 8. The non-i.i.d. case; 9. Rates of convergence for least squares estimators; 10. Penalties and sieves; 11. Some applications to semi-parametric models; 12. M-estimators; Appendix; References; Author index; Subject index; List of symbols.
£44.64
Cambridge University Press Tables of the Ordinates and Probability Integral of the Distribution of the Correlation Coefficient in Small Samples
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£35.14
Cambridge University Press Control Theory and Dynamic Games in Economic Policy Analysis
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£42.74
Cambridge University Press Random Matrices High Dimensional Phenomena 367 London Mathematical Society Lecture Note Series Series Number 367
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£51.99
Cambridge University Press Stopping Times and Directed Processes 47 Encyclopedia of Mathematics and its Applications Series Number 47
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£48.44
Cambridge University Press Pade Approximants 59 Encyclopedia of Mathematics and its Applications Series Number 59
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£103.94
Cambridge University Press Regression Modeling with Actuarial and Financial Applications Author Edward W Frees Nov2009
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£54.14
Cambridge University Press Exponential Random Graph Models for Social Networks Theory Methods and Applications 35 Structural Analysis in the Social Sciences Series Number 35
Book SynopsisExponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide a self-contained, exhaustive account of the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGMs. The authors supply the reader with sufficient detail to specify ERGMs, fit them to data with any of the available software packages and interpret the results.Trade Review'I've been waiting impatiently for this book and I was definitely not disappointed. Finally we have a sourcebook on ERGMs that is both comprehensive and comprehensible. Most of the chapters are written for quantitative researchers who are not statisticians. Many illustrative empirical applications are worked through. Software packages are discussed. For the researcher who is intrigued by the possibility of analyzing network data with an ERGM, or who is already trying to do so, this is an indispensable resource.' Peter Carrington, University of Waterloo'This collection offers readers an intuitive understanding of ERGMs, followed by a formal explanation of their statistical underpinnings as well as a methodological cookbook based on current software. Next, network scholars at the forefront of advancing theoretical and methodological contributions present eight compelling empirical studies. These studies illustrate how ERGMs offer exciting opportunities to advance theoretical understandings of network phenomena at the intra-organizational, inter-organizational, and societal levels.' Noshir Contractor, Jane S. and William J. White Professor of Behavioral Sciences, Northwestern University'p*, the exponential family of random graph distributions introduced by Frank and Strauss in 1986, has indeed become the best statistical model in network science. This edited volume is a must-have - Lusher, Koskinen, and Robins have put together a thorough compilation for both the p* novice and enthusiast. It is the handbook to own - and use!' Stanley Wasserman, Indiana UniversityTable of ContentsIntroduction Dean Lusher, Johan Koskinen and Garry Robins; 1. What are exponential random graph models Garry Robins and Dean Lusher; 2. The formation of social network structure Dean Lusher and Garry Robins; 3. A simplified account of ERGM as a statistical model Garry Robins and Dean Lusher; 4. An example of ERGM analysis Dean Lusher and Garry Robins; 5. Exponential random graph model fundamentals Johan Koskinene and Galina Daraganova; 6. Dependence graphs and sufficient statistics Johan Koskinen and Galina Daraganova; 7. Social selection, dyadic covariates and geospatial effects Garry Robins and Galina Daraganova; 8. Autologistic actor attribute models Galina Daraganova and Garry Robins; 9. ERGM extensions: models for multiple networks and bipartite networks Peng Wang; 10. Longitudinal models Tom Snijders and Johan Koskinen; 11. Simulation, estimation and goodness of fit Johan Koskinen and Tom Snijders; 12. Illustrations: simulation, estimation and goodness of fit Garry Robins and Dean Lusher; 13. Personal attitudes, perceived attitudes and social structures: a social selection model Dean Lusher and Garry Robins; 14. How to close a hole: exploring alternative closure mechanisms in inter-organizational networks Alessandro Lomi and Francesca Pallotti; 15. Interdependencies between working relations: multivariate ERGMs for advice and satisfaction Yu Zhao and Olaf Rank; 16. Brain, brawn or optimism? The structure and correlates of emergent military leadership Yuval Kalish and Gil Luria; 17. An ALAAM analysis of unemployment: the dual importance of who you know and where you live Galina Daraganova and Philippa Pattison; 18. Longitudinal changes in face-to-face and text message-mediated friendship networks Tasuku Igarashi; 19. The differential impact of directors' social and financial capital on corporate interlock formation Nicholas Harrigan and Matthew Bond; 20. Comparing networks: a structural correspondence between behavioural and recall networks Eric Quintane; 21. Modelling social networks: next steps Philippa Pattison and Tom Snijders.
£29.44
Cambridge University Press Stochastic Integration with Jumps 89 Encyclopedia of Mathematics and its Applications Series Number 89
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£70.82
Cambridge University Press The Essential Guide to Effect Sizes Statistical
Book SynopsisThis succinct and jargon-free introduction to effect sizes gives students and researchers the tools they need to interpret the practical significance of their results. Using a class-tested approach that includes numerous examples and step-by-step exercises, it introduces and explains three of the most important issues relating to the practical significance of research results: the reporting and interpretation of effect sizes (Part I), the analysis of statistical power (Part II), and the meta-analytic pooling of effect size estimates drawn from different studies (Part III). The book concludes with a handy list of recommendations for those actively engaged in or currently preparing research projects.Trade Review'Paul Ellis writes with a light touch, explains well, and uses numerous practical examples. He focuses on four of the issues that are central to the statistical changes now sweeping many disciplines - effect sizes, confidence intervals, power, and meta-analysis. This is a highly readable, highly practical book. It will be invaluable to anyone who wishes to contribute to - or even just understand - the research of the future.' Geoff Cumming, La Trobe University, Australia'Assessing the substantive significance of research is essential for both scientific progress and practical implications. This authoritative and well-written book gives relevant examples of key issues and offers practical guidelines for assessing the importance of research findings. The book concludes with clear recommendations for designing and carrying out good research and for assessing and reporting research findings.' William H. Starbuck, University of Oregon and Professor Emeritus, New York UniversityTable of ContentsList of figures; List of tables; List of boxes; Introduction; Part I. Effect Sizes and the Interpretation of Results: 1. Introduction to effect sizes; 2. Interpreting effects; Part II. The Analysis of Statistical Power: 3. Power analysis and the detection of effects; 4. The painful lessons of power research; Part III. Meta-Analysis: 5. Drawing conclusions using meta-analysis; 6. Minimizing bias in meta-analysis; Last word: thirty recommendations for researchers; Appendices: 1. Minimum sample sizes; 2. Alternative methods for meta-analysis; Bibliography; Index.
£36.09
Cambridge University Press Statistics for Anthropology
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£41.79
Cambridge University Press Bayesian Logical Data Analysis for the Physical Sciences
Book SynopsisIncreasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. Background material is provided in appendices and supporting Mathematica notebooks are available.Trade Review'As well as the usual topics to be found in a text on Bayesian inference, chapters are included on frequentist inference (for contrast), non-linear model fitting, spectral analysis and Poisson sampling.' Zentralblatt MATH'The examples are well integrated with the text and are enlightening.' Contemporary Physics'The book can easily keep the readers amazed and attracted to its content throughout the read and make them want to return back to it recursively. It presents a perfect balance between theoretical inference and a practical know-how approach to Bayesian methods.' Stan Lipovetsky, TechnometricsTable of ContentsPreface; Acknowledgements; 1. Role of probability theory in science; 2. Probability theory as extended logic; 3. The how-to of Bayesian inference; 4. Assigning probabilities; 5. Frequentist statistical inference; 6. What is a statistic?; 7. Frequentist hypothesis testing; 8. Maximum entropy probabilities; 9. Bayesian inference (Gaussian errors); 10. Linear model fitting (Gaussian errors); 11. Nonlinear model fitting; 12. Markov Chain Monte Carlo; 13. Bayesian spectral analysis; 14. Bayesian inference (Poisson sampling); Appendix A. Singular value decomposition; Appendix B. Discrete Fourier transforms; Appendix C. Difference in two samples; Appendix D. Poisson ON/OFF details; Appendix E. Multivariate Gaussian from maximum entropy; References; Index.
£59.84
Cambridge University Press Several Complex Variables
Book SynopsisFirst published in 2000, this book provides a clear and complete picture of research in Several Complex Variables and its interactions with PDEs, algebraic geometry, number theory, and differential geometry. The expository nature of the articles makes this an excellent introduction for students as well as a basis for continuing research.Table of ContentsPreface; 1. Local holomorphic equivalence of real analytic submanifolds in CN M. Salah Baouendi and Linda Preiss Rothschild; 2. How to use cycle space in complex geometry Daniel Barlet; 3. Resolution of singularities Edward Bierstone and Pierre D. Milman; 4. Global regularity of the ∂-Neuman problem: a survey of the L2-Sobolev theory Harold P. Boas and Emial J. Straube; 5. Recent developments in the classification theory of compact Käehler manifolds Frederic Campana and Thomas Peternell; 6. Remarks on global irregularity in the ∂-Neumann problem Michael Christ; 7. Subelliptic estimates and finite type John P. D'Angelo and Joseph J. Kohn; 8. Pseudoconvex-concave duality and regularization of currents Jean-Pierre Demailly; 9. Complex dynamics in higher dimension John Erik Fornaess and Nessim Sibony; 10. Attractors in Ρ2 John Erik Fornaess and Brendan Weickert; 11. Analytic Hilbert quotients Peter Heinzner and Alan Huckleberry; 12. Varieties of minimal rational tangents on uniruled projective manifolds Jun-Muk Hwang and Ngaiming Mok; 13. Recent developments in Seiberg–Witten theory and complex geometry Christian Okonek and Andrei Teleman; 14. Recent techniques in hyperbolicity problems Yum-Tong Siu; 15. Rigidity theorems in Käehler geometry and fundamental groups of varieties Domingo Toledo; 16. Nevanlinna theory and diophantine approximation Paul Vojta.
£49.39
Cambridge University Press Probabilistic Reasoning in Multiagent Systems
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£42.74
Cambridge University Press The Principle of Relativity
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£35.14
Cambridge University Press Combinatorial Methods in Discrete Mathematics 55 Encyclopedia of Mathematics and its Applications Series Number 55
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£51.29
Cambridge University Press Portfolio Theory and Risk Management Mastering Mathematical Finance
Book SynopsisWith its emphasis on examples, exercises and calculations, this book suits advanced undergraduates as well as postgraduates and practitioners. It provides a clear treatment of the scope and limitations of mean-variance portfolio theory and introduces popular modern risk measures. Proofs are given in detail, assuming only modest mathematical background, but with attention to clarity and rigour. The discussion of VaR and its more robust generalizations, such as AVaR, brings recent developments in risk measures within range of some undergraduate courses and includes a novel discussion of reducing VaR and AVaR by means of hedging techniques. A moderate pace, careful motivation and more than 70 exercises give students confidence in handling risk assessments in modern finance. Solutions and additional materials for instructors are available at www.cambridge.org/9781107003675.Table of ContentsPreface; 1. Risk and return; 2. Portfolios consisting of two assets; 3. Lagrange multipliers; 4. Portfolios of multiple assets; 5. The capital asset pricing model; 6. Utility functions; 7. Value at risk; 8. Coherent measures of risk; Index.
£35.14
Cambridge University Press Computation and Automata 25 Encyclopedia of Mathematics and its Applications Series Number 25
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£65.54
Cambridge University Press Product Integration With Application to Differential Equations 10 Encyclopedia of Mathematics and its Applications Series Number 10
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£60.89
Cambridge University Press Statistics Explained An Introductory Guide for Life Scientists
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£33.24
Cambridge University Press Association Schemes Designed Experiments Algebra and Combinatorics 84 Cambridge Studies in Advanced Mathematics Series Number 84
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£45.59
Cambridge University Press Introduction to Statistical Methods for Biosurveillance
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£47.49
Cambridge University Press Digital Nets and Sequences
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£85.49
Cambridge University Press Exponential Random Graph Models for Social Networks Theory Methods and Applications 35 Structural Analysis in the Social Sciences Series Number 35
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£67.45
Cambridge University Press The Essential Guide to Effect Sizes Statistical Power MetaAnalysis and the Interpretation of Research Results
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£90.25
Cambridge University Press An Outline of Ergodic Theory 122 Cambridge Studies in Advanced Mathematics Series Number 122
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£55.09
Cambridge University Press An Introduction to Random Matrices 118 Cambridge Studies in Advanced Mathematics Series Number 118
Book SynopsisThe theory of random matrices plays an important role in many areas of pure mathematics and employs a variety of sophisticated mathematical tools (analytical, probabilistic and combinatorial). This diverse array of tools, while attesting to the vitality of the field, presents several formidable obstacles to the newcomer, and even the expert probabilist. This rigorous introduction to the basic theory is sufficiently self-contained to be accessible to graduate students in mathematics or related sciences, who have mastered probability theory at the graduate level, but have not necessarily been exposed to advanced notions of functional analysis, algebra or geometry. Useful background material is collected in the appendices and exercises are also included throughout to test the reader's understanding. Enumerative techniques, stochastic analysis, large deviations, concentration inequalities, disintegration and Lie algebras all are introduced in the text, which will enable readers to approachTrade Review' … this is a very valuable new reference for the subject, incorporating many modern results and perspectives that are not present in earlier texts on this topic … this book would serve as an excellent foundation with which to begin studying other aspects of random matrix theory.' Terence Tao, Mathematical Reviews'… the book aims to introduce some of the modern techniques of random matrix theory in a comprehensive and rigorous way. It has a broad range of topics and most of them are fairly accessible. The focus is on introducing and explaining the main techniques, rather than obtaining the most general results. Additional references are given for the reader who wants to continue the study of a certain topic. The writing style is careful and the book is mostly self-contained with complete proofs. This is an excellent new contribution to random matrix theory.' Journal of Approximation TheoryTable of ContentsPreface; 1. Introduction; 2. Real and complex Wigner matrices; 3. Hermite polynomials, spacings, and limit distributions for the Gaussian ensembles; 4. Some generalities; 5. Free probability; Appendices; Bibliography; General conventions; Glossary; Index.
£63.64
Cambridge University Press DataHandling in Biomedical Science
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£61.75
Cambridge University Press Bayesian Time Series Models
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£101.65
Cambridge University Press LMS12 Syposium on Complex Analysis London Mathematical Society Lecture Note Series Series Number 12
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£55.09
Cambridge University Press Complex Analysis and Algebraic Geometry
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£122.55
Cambridge University Press LMS 45 Recursion Theory Applns London Mathematical Society Lecture Note Series Series Number 45
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£69.99
Cambridge University Press Comparison of Statistical Experiments 36 Encyclopedia of Mathematics and its Applications Series Number 36
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£212.80
Cambridge University Press Estimation Inference and Specification Analysis 22 Econometric Society Monographs
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£77.90
Cambridge University Press An Introduction to Probability Theory 001
Book SynopsisProfessor Ità is one of the most distinguished probability theorists in the world, and in this modern, concise introduction to the subject he explains basic probabilistic concepts rigorously and yet gives at the same time an intuitive understanding of random phenomena. In the first chapter he considers finite situations, but from an advanced standpoint that enables the transition to greater generality to be achieved more easily. Chapter 2 deals with probability measures and includes a discussion of the fundamental concepts of probability theory. These concepts are formulated abstractly but without sacrificing intuition. The last chapter is devoted to infinite sums of independent real random variables. Each chapter is divided into sections that end with a set of problems with hints for solution. This textbook will be particularly valuable to students of mathematics taking courses in probability theory who need a modern introduction to the subject that yet does not allow overemphasis on Table of ContentsPreface; 1. Finite trials; 2. Probability measures; 3. Fundamental concepts in probability theory; 4. Sums of independent random variables; Index.
£41.79
Cambridge University Press Models of Category Counts
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£27.76
Cambridge University Press LMS 89 An F Space Sampler London Mathematical Society Lecture Note Series Series Number 89
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£79.10
Cambridge University Press A Second Course on Real Functions
Book SynopsisWhen considering a mathematical theorem one ought not only to know how to prove it but also why and whether any given conditions are necessary. All too often little attention is paid to to this side of the theory and in writing this account of the theory of real functions the authors hope to rectify matters.Table of Contents1. Monotone functions; 2. Subsets of R; 3. Continuity; 4. Differentiation; 5. Borel measurability; 6. Integration.
£38.94
Cambridge University Press LMS 76 Spectral Thry Linear Operts London Mathematical Society Lecture Note Series Series Number 76
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£74.13
Cambridge University Press Statistical Tables for the Social Biological and Physical Sciences
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£35.14