From the medicine we take, the treatments we receive, the aptitude and psychometric tests given by employers, the cars we drive, the clothes we wear to even the beer we drink, statistics have given shape to the world we inhabit. For the media, statistics are routinely 'damning', 'horrifying', or, occasionally, 'encouraging'. Yet, for all their ubiquity, most of us really don't know what to make of statistics. Exploring the history, mathematics, philosophy and practical use of statistics, Eileen Magnello - accompanied by Bill Mayblin's intelligent graphic illustration - traces the rise of statistics from the ancient Babylonians, Egyptians and Chinese, to the censuses of Romans and the Greeks, and the modern emergence of the term itself in Europe. She explores the 'vital statistics' of, in particular, William Farr, and the mathematical statistics of Karl Pearson and R.A. Fisher.She even tells how knowledge of statistics can prolong one's life, as it did for evolutionary biologist Stephen Jay Gould, given eight months to live after a cancer diagnoses in 1982 - and he lived until 2002. This title offers an enjoyable, surprise-filled tour through a subject that is both fascinating and crucial to understanding our world.
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This wide-ranging, jargon-free dictionary contains over 2,300 entries on all aspects of statistics, including terms used in computing, mathematics, and probability. It also includes biographical information on over 200 key figures in the field and coverage of statistical journals and societies. While embracing the whole multi-disciplinary spectrum of this complex subject, information is presented in a clear and practical manner. This edition features recommended web links for many entries, accessible via the Dictionary of Statistics website, which provide valuable extra information. This edition features expanded coverage of applied statistics. Entries are generously illustrated with 130 useful figures and diagrams, and include worked examples where applicable. Appendices include a historical calendar of important statistical events, lists of statistical and mathematical notation, and statistical tables. It is an invaluable dictionary for statistics students and professionals from a wide range of disciplines, including economics, politics, market research, medicine, psychology, pharmaceuticals, and mathematics, and provides a clear introduction to the subject for the general reader.
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Need to learn statistics as part of your job, or want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone who's new to the subject. This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. Each chapter in this thoroughly revised and expanded edition presents easy-to-follow descriptions illustrated by graphics, formulas, and lots of solved examples. Before you know it, you'll learn to apply statistical reasoning and statistical techniques, from basic concepts of probability and hypothesis testing to multivariate analysis. Statistics in a Nutshell includes: Introductory material - Learn basic concepts of measurement and probability theory, data management for statistical analysis, research design and experimental design, how to write up your own results, and how to critique statistics presented by others Basic inferential statistics - Discover the concepts of hypothesis testing, simple correlation, the distinction between parametric and nonparametric statistics, and learn simple methods of analysis appropriate to dichotomous, categorical, and continuous variables Advanced inferential techniques - Learn the General Linear Model, including analysis of Variance (ANOVA), multiple linear regression, and logistic and multinomial regression Specialized techniques - Use and interpret business and quality improvement statistics, medical and public health statistics, and educational and psychological statistics If you need to know how to perform most common statistical analyses, and how to use a wide range of statistical techniques without getting in over your head, this is the book for you.
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Why is it that incredibly unlikely phenomena actually happen quite regularly and why should we, in fact, expect such things to happen? Here, in this highly original book - aimed squarely at anyone with an interest in coincidences, probability or gambling - eminent statistician David Hand answers this question by weaving together various strands of probability into a unified explanation, which he calls the improbability principle. This is a book that will appeal not only to those who love stories about startling coincidences and extraordinarily rare events, but also to those who are interested in how a single bold idea links areas as diverse as gambling, the weather, airline disasters and creative writing as well as the origin of life and even the universe. The Improbability Principle will change your perspective on how the world works - and tell you what the Bible code and Shakespeare have in common, how to win the lottery, why Apple's song shuffling was made less random to seem more random. Oh and why lightning does in fact strike twice...
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Everyone knows that abuse of statistics is rampant in popular media. Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists- yes, even those published in peer-reviewed journals- are doing statistics wrong. Statistics Done Wrong comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes. In this book, you'll learn: Why "statistically significant" doesn't necessarily imply practical significance Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas How and how not to ask questions, design experiments, and work with data Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates Why false positives are much more common than "significant at the 5% level" would suggest By walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, Statistics Done Wrong will teach you how to be a better analyst, data scientist, or researcher.
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The introduction to statistics that psychology students can't afford to be without Understanding statistics is a requirement for obtaining and making the most of a degree in psychology, a fact of life that often takes first year psychology students by surprise. Filled with jargon-free explanations and real-life examples, Psychology Statistics For Dummies makes the often-confusing world of statistics a lot less baffling, and provides you with the step-by-step instructions necessary for carrying out data analysis. Psychology Statistics For Dummies:* Serves as an easily accessible supplement to doorstop-sized psychology textbooks* Provides psychology students with psychology-specific statistics instruction* Includes clear explanations and instruction on performing statistical analysis* Teaches students how to analyze their data with SPSS, the most widely used statistical packages among students
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Modern statistics is very different from the dry and dusty discipline of the popular imagination. In its place is an exciting subject which uses deep theory and powerful software tools to shed light and enable understanding. And it sheds this light on all aspects of our lives, enabling astronomers to explore the origins of the universe, archaeologists to investigate ancient civilisations, governments to understand how to benefit and improve society, and businesses to learn how best to provide goods and services. Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.
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The ultimate beginner's guide to SPSS and statistical analysis SPSS Statistics For Dummies is the fun and friendly guide to mastering SPSS. This book contains everything you need to know to get up and running quickly with this industry-leading software, with clear, helpful guidance on working with both the software and your data. Every chapter of this new edition has been updated with screenshots and steps that align with SPSS 23.0. You'll learn how to set up the software and organize your workflow, then delve deep into analysis to discover the power of SPSS capabilities. You'll discover the mechanics behind the calculations, perform predictive analysis, produce informative graphs, and maximize your data, even if it's been awhile since your last statistics class. SPSS is the leading statistical software for social sciences, marketing, health care, demography, government, education, data mining, and more. This powerful package gives you the tools you need to get more out of your data, and this book is your beginner-friendly guide to getting the most out of the software. Install and configure SPSS and learn the basics of how it works Master the process of getting data into SPSS and manipulating it to produce results See how to display data in dozens of different graphic formats to fit specific needs Make SPSS manufacture the numbers you want and take advantage of the many analysis options Discover ways to customize the SPSS interface and the look of your results, edit graphics and pivot tables, and program SPSS with Command Syntax Statistical analysis is crucial to so many industries, and accuracy and efficiency are crucial. SPSS offers you the capability to deliver, but you still must know how to take utmost advantage of the tools at your fingertips. SPSS Statistics For Dummies shows you how to handle data like a pro, with step-by-step instruction and expert advice.
The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word "statistics" alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining without losing your cool. * Helps you to identify valid, useful, and understandable patterns in data * Provides guidance on extracting previously unknown information from large databases * Shows you how to discover patterns available in big data * Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.
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This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: * Analysis and application of univariate financial time series * The return series of multiple assets * Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.
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This monograph introduces methods for handling filtering and control problems in nonlinear stochastic systems arising from network-induced phenomena consequent on limited communication capacity. Such phenomena include communication delay, packet dropout, signal quantization or saturation, randomly occurring nonlinearities and randomly occurring uncertainties. The text is self-contained, beginning with an introduction to nonlinear stochastic systems, network-induced phenomena and filtering and control, moving through a collection of the latest research results which focuses on the three aspects of: * the state-of-the-art of nonlinear filtering and control; * recent advances in recursive filtering and sliding mode control; and * their potential for application in networked control systems, and concluding with some ideas for future research work. New concepts such as the randomly occurring uncertainty and the probability-constrained performance index are proposed to make the network models as realistic as possible. The power of combinations of such recent tools as the completing-the-square and sums-of-squares techniques, Hamilton-Jacobi-Isaacs matrix inequalities, difference linear matrix inequalities and parameter-dependent matrix inequalities is exploited in treating the mathematical and computational challenges arising from nonlinearity and stochasticity. Nonlinear Stochastic Systems with Network-Induced Phenomena establishes a unified framework of control and filtering which will be of value to academic researchers in bringing structure to problems associated with an important class of networked system and offering new means of solving them. The significance of the new concepts, models and methods presented for practical control engineering and signal processing will also make it a valuable reference for engineers dealing with nonlinear control and filtering problems.
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Inequalities based on Sobolev Representations deals exclusively with very general tight integral inequalities of Chebyshev-Gruss, Ostrowski types and of integral means, all of which depend upon the Sobolev integral representations of functions. Applications illustrate inequalities that engage in ordinary and weak partial derivatives of the involved functions. This book also derives important estimates for the averaged Taylor polynomials and remainders of Sobolev integral representations. The results are examined in all directions and through both univariate and multivariate cases. This book is suitable for researchers, graduate students, and seminars in subareas of mathematical analysis, inequalities, partial differential equations and information theory.
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A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: * A chapter on the analysis of correlated outcome data * A wealth of additional material for topics ranging from Bayesian methods to assessing model fit * Rich data sets from real-world studies that demonstrate each method under discussion * Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
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If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. You'll work with a case study throughout the book to help you learn the entire data analysis process-from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts. The new edition switches over to Pandas for data processing. It also includes new chapters on multiple regression, survival analysis, missing value imputation and resampling. Develop your understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Learn topics not usually covered in an introductory course, such as Bayesian estimation Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data
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WHAT ARE THE ODDS YOU'LL WIN THE LOTTERY? How long will your kids wait in line at Disney World? Who decides that "standardized tests" are fair? Why do highway engineers build slow-moving ramps? What does it mean, statistically, to be an "Average Joe"? NUMBERS RULE YOUR WORLD In the popular tradition of eye-opening bestsellers like Freakonomics, The Tipping Point, and Super Crunchers, this fascinating book from renowned statistician and blogger Kaiser Fung takes you inside the hidden world of facts and figures that affect you every day, in every way. These are the statistics that rule your life, your job, your commute, your vacation, your food, your health, your money, and your success. This is how engineers calculate your quality of living, how corporations determine your needs, and how politicians estimate your opinions. These are the numbers you never think about-even though they play a crucial role in every single aspect of your life. What you learn may surprise you, amuse you, or even enrage you. But there's one thing you won't be able to deny: Numbers Rule Your World..."An easy read with a big benefit." -Fareed Zakaria, CNN "For those who have anxiety about how organization data-mining is impacting their world, Kaiser Fung pulls back the curtain to reveal the good and the bad of predictive analytics." -Ian Ayres,Yale professor and author of Super Crunchers: Why Thinking By Numbers is the New Way to Be Smart "A book that engages us with stories that a journalist would write, the compelling stories behind the stories as illuminated by the numbers, and the dynamics that the numbers reveal." -John Sall, Executive Vice President, SAS Institute "Little did I suspect, when I picked up Kaiser Fung's book, that I would become so entranced by it - an illuminating and accessible exploration of the power of statistical analysis for those of us who have no prior training in a field that he explores so ably." -Peter Clarke, author of Keynes: The Rise, Fall, and Return of the 20th Century's Most Influential Economist "A tremendous book...If you want to understand how to use statistics, how to think with numbers and yet to do this without getting lost in equations, if you've been looking for the book to unlock the door to logical thinking about problems, well, you will be pleased to know that you are holding that book in your hands. " -Daniel Finkelstein, Executive Editor, The Times of London "I thoroughly enjoyed this accessible book and enthusiastically recommendit to anyone looking to understand and appreciate the role of statistics and dataanalysis in solving problems and in creating a better world." -Michael Sherman, Texas A&M University, American Statistician
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A pioneer of artificial intelligence shows how the study of causality revolutionized science and the world 'Correlation does not imply causation.' This mantra was invoked by scientists for decades in order to avoid taking positions as to whether one thing caused another, such as smoking and cancer and carbon dioxide and global warming. But today, that taboo is dead. The causal revolution, sparked by world-renowned computer scientist Judea Pearl and his colleagues, has cut through a century of confusion and placed cause and effect on a firm scientific basis. Now, Pearl and science journalist Dana Mackenzie explain causal thinking to general readers for the first time, showing how it allows us to explore the world that is and the worlds that could have been. It is the essence of human and artificial intelligence. And just as Pearl's discoveries have enabled machines to think better, The Book of Why explains how we can think better.
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If you know how to program with Python and also know a little about probability, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you'll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book's computational approach helps you get a solid start. Use your existing programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.
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Understanding the world of R programming and analysis has never been easier Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses as well as step-by-step guidance that shows you exactly how to implement them using R programming. People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results. * Gets you up to speed on the #1 analytics/data science software tool * Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling * Shows you how R offers intel from leading researchers in data science, free of charge * Provides information on using R Studio to work with R Get ready to use R to crunch and analyze your data the fast and easy way!
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Tough Test Questions? Missed Lectures? Not Enough Time? Fortunately, there's Schaum's. This all-in-one-package includes more than 400 fully solved problems, examples, and practice exercises to sharpen your problem-solving skills. Plus, you will have access to 20 detailed videos featuring instructors who explain the most commonly tested problems - it's just like having your own virtual tutor! You'll find everything you need to build confidence, skills, and knowledge for the highest score possible. More than 40 million students have trusted Schaum's to help them succeed in the classroom and on exams. Schaum's is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. You also get hundreds of examples, solved problems, and practice exercises to test your skills. This Schaum's Outline gives you: 405 fully solved problems; clear, concise explanations of all probability, variables, and processes concepts; and support for all the major textbooks in the subject areas. Fully compatible with your classroom text, Schaum's highlights all the important facts you need to know. Use Schaum's to shorten your study time - and get your best test scores! Schaum's Outlines - Problem Solved.
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The ideal review for your probability course More than 40 million students have trusted Schaum's Outlines for their expert knowledge and helpful solved problems. Written by renowned experts in their respective fields, Schaum's Outlines cover everything from math to science, nursing to language. The main feature for all these books is the solved problems. Step-by-step, authors walk readers through coming up with solutions to exercises in their topic of choice. Outline format supplies a concise guide to the standard college course in probability 430 solved problems Supports all the major textbooks for Probability courses Clear, concise explanations of all Probability concepts Appropriate for the following courses: Elementary Probability & Statistics; Data Analysis; Finite Mathematics; Introduction to Mathematical Statistics; Mathematics for Biological Sciences; Introductory Statistics; Discrete Mathematics; Probability for Applied Science; Introduction to Probability Theory
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We underestimate the importance of luck in our lives. We think too highly of the golfer who wins the British Open and, if he loses the next tournament, we speculate that he slacked off. Although the winner is surely an excellent golfer, good luck in how the ball bounced and how it rolled afterwards outside of the golfer's control also played an important role.An insufficient appreciation of chance can wreak all kinds of mischief - not only in sports, but also education, medicine, business, politics and elsewhere. Perfectly natural, random variation can lead us to attach meaning to the meaningless.Freakonomics showed how economic calculations can explain seemingly counter intuitive decision-making. Thinking, Fast and Slow, helped readers identify a host of small cognitive errors that can lead to miscalculations and irrational thought. In What the Luck? statistician and author, Gary Smith, sets himself a similar goal, and explains - in clear, understandable, and witty prose - how a statistical understanding of luck can change the way we see just about every aspect of our lives.
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Score higher in your business statistics course? Easy. Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons. Business Statistics For Dummies tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, with lots of examples that shows you how these concepts apply to the world of global business and economics. * Shows you how to use statistical data to get an informed and unbiased picture of the market * Serves as an excellent supplement to classroom learning * Helps you score your highest in your Business Statistics course If you're studying business at the university level or you're a professional looking for a desk reference on this complicated topic, Business Statistics For Dummies has you covered.
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Statistics For Dummies, 2nd Edition (9781119293521) was previously published as Statistics For Dummies, 2nd Edition (9780470911082). While this version features a new Dummies cover and design, the content is the same as the prior release and should not be considered a new or updated product. The fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. * Tracks to a typical first semester statistics course * Updated examples resonate with today's students * Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.
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Chance, risk, uncertainty: they're all part of our lives, whether we're in business or on the school run, deciding future strategy or just the best route home. Sometimes their effects are intriguing: a streak of extraordinary luck, say, or some bizarre coincidence. More often they just leave us confused, unnerved - even anxious. When is a series of odd events mere happenstance, or something more significant? How do we make sense of the ever-changing evidence about what's good or bad for us? Just how reliable are predictions of weather, climate and elections - and how should we respond to them? In this book, award-winning scientist and writer Robert Matthews shows how we can cut through such conundrums using some of the most potent intellectual tools ever developed: the laws of probability. Using real-life examples, he shows how to wield them to: Understand and even predict coincidences Tell when insurance policies are worth having Make sense of medical tests and scientific 'breakthroughs' Judge when "expert" evidence is compelling or questionable Make decisions about everything from sports betting to weather forecasts Professor Matthews also gives a groundbreaking introduction to the power of Bayes's Theorem, whose ability to turn evidence into insight is now transforming our lives - and helping to unmask a major scientific scandal.
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