The worlds of Wall Street & The City have always held a certain allure but in recent years have left an indelible mark on the wider public consciousness & there has been a need to become more financially literate The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types whether for general interest or because of the enormous monetary rewards on offer An Introduction to Quantitative Finance concerns financial derivatives
- a derivative being a contract between two entities whose value derives from the price of an underlying financial asset
- & the probabilistic tools that were developed to analyse them The theory in the text is motivated by a desire to provide a suitably rigorous yet accessible foundation to tackle problems the author encountered whilst trading derivatives on Wall Street The book combines an unusual blend of real-world derivatives trading experience & rigorous academic background Probability provides the key tools for analysing & valuing derivatives The price of a derivative is closely linked to the expected value of its pay-out & suitably scaled derivative prices are martingales fundamentally important objects in probability theory The prerequisite for mastering the material is an introductory undergraduate course in probability The book is otherwise self-contained & in particular requires no additional preparation or exposure to finance It is suitable for a one-semester course quickly exposing readers to powerful theory & substantive problems The book may also appeal to students who have enjoyed probability & have a desire to see how it can be applied Signposts are given throughout the text to more advanced topics & to different approaches for those looking to take the subject further

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This concise accessible introduction to quantum computing is aimed at advanced undergraduate & beginning graduate students from a variety of scientific backgrounds The text is technically detailed & clearly illustrated throughout with diagrams & exercises 288 pages numerous line drawings Kaye Phillip (Institute for Quantum Computing University of Waterloo Ontario Canada) ...

An Introduction to Quantum Field Theory is a textbook intended for the graduate physics course covering relativistic quantum mechanics quantum electrodynamics & Feynman diagrams The authors make these subjects accessible through carefully worked examples illustrating the technical aspects of the subject & intuitive explanations of what is going on behind the mathematics After presenting the basics of quantum electrodynamics the authors discuss the theory of renormalization & its relation to statistical mechanics & introduce the renormalization group This discussion sets the stage for a discussion of the physical principles that underlie the fundamental interactions of elementary particle physics & their description by gauge field theories ...

In an age of big data data journalism & with a wealth of quantitative information around us it is not enough for students to be taught only 100 year old statistical methods using 'out of the box' software They need to have 21st-century analytical skills too This is an excellent & student-friendly text from two of the world leaders in the teaching & development of spatial analysis It shows clearly why the open source software R is not just an alternative to commercial GIS it may actually be the better choice for mapping analysis & for replicable research Providing practical tips as well as fully working code this is a practical 'how to' guide ideal for undergraduates as well as those using R for the first time It will be required reading on my own courses- Richard Harris Professor of Quantitative Social Science University of Bristol R is a powerful open source computing tool that supports geographical analysis & mapping for the many geography & non-geography' students & researchers interested in spatial analysis & mapping This book provides an introduction to the use of R for spatial statistical analysis geocomputation & the analysis of geographical information for researchers collecting & using data with location attached largely through increased GPS functionality Brunsdon & Comber take readers from zero to hero' in spatial analysis & mapping through functions they have developed & compiled into R packages This enables practical R applications in GIS spatial analyses spatial statistics mapping & web-scraping Each chapter
Includes: Example data & commands for exploring it Scripts & coding to exemplify specific functionality Advice for developing greater understanding
- through functions such as locator () View () & alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text This is a definitive 'how to' that takes students
- of any discipline
- from coding to actual applications & uses of R



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Covers a broad range of subjects that undergraduates in the discipline should be familiar & comfortable with upon graduation From chapters on the scientific method & fundamental research concepts to experimental design sampling & statistical analysis the text offers an excellent introduction to the key concepts of geographical research The content is applicable for students at the beginning of their studies right through to planning & conducting dissertations The book has also been of particular support in designing my level 1 & 2 tutorials which cover similar ground to several of the chapters- Joseph Mallalieu School of Geography Leeds University Montello & Sutton is one of the best texts I've used in seminars on research methodology The text offers a clear balance of quantitative vs qualitative & physical vs human which I've found particularly valuable The chapters on research ethics scientific communication information technologies & data visualization are excellent
- Kenneth E Foote Department of Geography University of Colorado at Boulder This is a broad & integrative introduction to the conduct & interpretation of scientific research covering both geography & environmental studies Written for undergraduate & postgraduate students it Explains both the conceptual & the technical aspects of research as well as all phases of the research process Combines approaches in physical geography & environmental science human geography & human-environment relations & geographic & environmental information techniques (such as GIS cartography & remote sensing) Combines natural & social scientific approaches common to subjects in geography & environmental studies
Includes: case studies of actual research projects to demonstrate the breadth of approaches taken It will be core reading for students studying scientific research methods in geography environmental studies & related disciplines such as planning & earth science

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For over 25 years An Introduction to Social Psychology has been combining traditional academic rigor with a contemporary level of cohesion accessibility pedagogy & instructor support to provide a definitive guide to the engaging & ever-evolving field of social psychology This sixth edition completely revised & updated to reflect current issues & underlying theory in the field has been specially designed to meet the needs of students at all levels with contributions written by leading psychologists each an acknowledged expert in the topics covered in a given chapter The text benefits hugely from an updated range of innovative pedagogical features intended to catch the imagination combined with a rigorous editorial approach which results in a cohesive & uniform style accessible to all Each chapter addresses both major themes & key studies showing how the relevant field of research has developed over time & linking classic & contemporary perspectives ...

Fully updated to reflect the most recent scholarship in the field & revised to include many more pedagogical features An Introduction to Sociolinguistics 7th Edition builds on its foundation as the most preeminent textbook in sociolinguistics updated for today s students Significantly revised discussions throughout each of the book s four key parts reflect the state of the field today

Includes:: new chapters on Pragmatics Discourse Analysis & Sociolinguistics & Education Incorporates innovative new perspectives drawn from linguistic anthropology Provides an accessible history of the development of sociolinguistic thought & how this fast-moving field is integral to our lives

Includes:: numerous opportunities for students to engage with ideas presented in the text through a new glossary new Explorations & end-of-chapter exercises links & key concepts New companion website

Includes:: links & resources for students





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This comprehensive flexible text is used in both one- & two-semester courses to review introductory through intermediate statistics Instructors select the topics that are most appropriate for their course Its conceptual approach helps students more easily understand the concepts & interpret SPSS & research results Key concepts are simply stated & occasionally reintroduced & related to one another for reinforcement Numerous examples demonstrate their relevance This edition features more explanation to increase understanding of the concepts Only crucial equations are included In addition to updating throughout the new edition features New co-author Debbie L Hahs-Vaughn the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award A new chapter on logistic regression models for today's more complex methodologies More on computing confidence intervals & conducting power analyses using GPower Many more SPSS screenshots to assist with understanding how to navigate SPSS & annotated SPSS output to assist in the interpretation of results Extended sections on how to write-up statistical results in APA format New learning tools including chapter-opening vignettes outlines & a list of key concepts many more examples tables & figures boxes & chapter summaries More tables of assumptions & the effects of their violation including how to test them in SPSS 33 new conceptual computational & all new interpretative problems A website that features Power Point slides answers to the even-numbered problems & test items for instructors & for students the chapter outlines key concepts & datasets that can be used in SPSS & other packages & more Each chapter begins with an outline a list of key concepts & a vignette related to those concepts Realistic examples from education & the behavioral sciences illustrate those concepts Each example examines the procedures & assumptions & provides instructions for how to run SPSS including annotated output & tips to develop an APA style write-up Useful tables of assumptions & the effects of their violation are included along with how to test assumptions in SPSS ' Stop & Think' boxes provide helpful tips for better understanding the concepts Each chapter

Includes:: computational conceptual & interpretive problems The data sets used in the examples & problems are provided on the web Answers to the odd-numbered problems are given in the book The first five chapters review descriptive statistics including ways of representing data graphically statistical measures the normal distribution & probability & sampling The remainder of the text covers inferential statistics involving means proportions variances & correlations basic & advanced analysis of variance & regression models Topics not dealt with in other texts such as robust methods multiple comparison & nonparametric procedures & advanced ANOVA & multiple & logistic regression models are also reviewed Intended for one- or two-semester courses in statistics taught in education andor the behavioral sciences at the graduate andor advanced undergraduate level knowledge of statistics is not a prerequisite A rudimentary knowledge of algebra is required

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning an essential toolset for making sense of the vast & complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years This book presents some of the most important modeling & prediction techniques along with relevant applications Topics include linear regression classification resampling methods shrinkage approaches tree-based methods support vector machines clustering & more Color graphics & real-world examples are used to illustrate the methods presented Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science industry & other fields each chapter contains a tutorial on implementing the analyses & methods presented in R an extremely popular open source statistical software platform Two of the authors co-wrote The Elements of Statistical Learning (Hastie Tibshirani & Friedman 2nd edition 2009) a popular reference book for statistics & machine learning researchers An Introduction to Statistical Learning covers many of the same topics but at a level accessible to a much broader audience This book is targeted at statisticians & non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data The text assumes only a previous course in linear regression & no knowledge of matrix algebra ...

Ott & Longnecker&s AN INTRODUCTION TO STATISTICAL METHODS & DATA ANALYSIS Seventh Edition provides a broad overview of statistical methods for advanced undergraduate & graduate students from a variety of disciplines who have little or no prior course work in statistics The authors teach students to solve problems encountered in research projects to make decisions based on data in general settings both within & beyond the university setting & to become critical readers of statistical analyses in research papers & news reports The first eleven chapters present material typically covered in an introductory statistics course as well as case studies & examples that are often encountered in undergraduate capstone courses The remaining chapters cover regression modeling & design of experiments ...