With its application-oriented approach, the fifth EMEA edition of Statistics for Business and Economics teaches students the core concepts of statistics in the fields of business, management, and economics, with the needs of the non-mathematician in mind.

The authors interweave statistical methodology with applications of data analysis to enrich students’ understanding of how statistics underpin problem-solving and decision-making. Students develop a computational foundation and learn to use various techniques before moving on to statistical application and interpretation.

At the end of each section, exercises focus on computation and the use of formulas, while application exercises require students to apply what they have learnt to real-world problems.

The text emphasises four themes to support evidence-based management decision making: 1. Setting the statistical landscape in a management context 2. Interpretative decision making based on patterns revealed by exploratory data analyses 3. Statistical decision making guided by the test-based findings of inferential analyses 4. Predictive decision making using statistical modelling evidence. The thread that links them is the role of data analytics as a management decision-support tool. This fifth edition builds on the strengths of the fourth edition by: - Highlighting newer trends in statistical applications in management practice - Strengthening the Excel-based generation of statistical evidence using a custom-built software product, called X-Static - Enhancing the graphic visualisation of statistical evidence. Target market: - Undergraduate students of Management at universities (BCom, BAcc, etc) - Management diploma students working towards professional qualifications at institutions such as the IMM, CSSA, CIMA, IAC, etc. - Postgraduate students (MBA and PGDip) of Management at business schools.

Economic theories can be expressed in words, numbers, graphs and symbols. The existing traditional economics textbooks cover all four methods, but the general focus is often more on writing about the theory and methods, with few practical examples. With an increasing number of universities having introduced mathematical economics at undergraduate level, Basic mathematics for economics students aims to fill this gap in the field. Basic mathematics for economics students begins with a comprehensive chapter on basic mathematical concepts and methods (suitable for self-study, revision or tutorial purposes) to ensure that students have the necessary foundation. The book is written in an accessible style and is extremely practical. Numerous mathematical economics examples and exercises are provided as well as fully worked solutions using numbers, graphs and symbols. Basic mathematics for economics students is aimed at all economics students. It focuses on quantitative aspects and especially complements the three highly popular theoretical economics textbooks, Understanding microeconomics, Understanding macroeconomics and Economics for South African students, all written by Philip Mohr and published by Van Schaik Publishers.

Statistics and quantitative methods are brought to life for social science students in this tutorial course.

,P> This revised edition provides an overview of entry- and intermediate-level statistics, and the material on the accompanying website provides extensive practice. Both the text and the website are structured to make learning self-directed, thus numerous worked examples, exercises, activities and tests are included. The emphasis, throughout, is on practice.

Students are expected to engage with the material and experience multiple aspects of data and statistical analysis. Most of the tutorials include detailed examples of how to conduct analyses in Microsoft Excel, SPSS, or R.

The established text Statistics for Management and Economics delivers an accessible and comprehensive overview for business students across the UK, Europe, the Middle East and Africa. With a wealth of examples and real data, this statistics textbook is essential reading for all business, management and economics courses at undergraduate and MBA level.

Keller's practical three-step approach to problem-solving demonstrates how statistics are vital for today's managers and economists: it teaches students how to identify the correct technique for a problem or data type, compute the statistics and how to interpret the results meaningfully, equipping them with the practical skills they need in a world of big data, data visualization and social media.

Integrated Population Biology and Modeling: Part A offers very complex and precise realities of quantifying modern and traditional methods of understanding populations and population dynamics. Chapters cover emerging topics of note, including Longevity dynamics, Modeling human-environment interactions, Survival Probabilities from 5-Year Cumulative Life Table Survival Ratios (Tx+5/Tx): Some Innovative Methodological Investigations, Cell migration Models, Evolutionary Dynamics of Cancer Cells, an Integrated approach for modeling of coastal lagoons: A case for Chilka Lake, India, Population and metapopulation dynamics, Mortality analysis: measures and models, Stationary Population Models, Are there biological and social limits to human longevity?, Probability models in biology, Stochastic Models in Population Biology, and more.

This text presents the 17th and concluding volume of the "Statistics Handbook". It covers order statistics, dealing primarily with applications. The book is divided into six parts as follows: results for specific distributions; linear estimation; inferential methods; prediction; goodness-of-fit tests; and applications. Theoretical advances have been made in this area of research, and order statistics has also found important applications in many diverse areas, these include life-testing and reliability, robustness studies, statistical quality control, filtering theory, signal processing, image processing, and radar target detection. A variety of theoretical researchers, statisticians and engineers have been brought together to produce this handbook, and the subject of order statistics has been split across volumes 16 and 17. Volume 17 focuses on applications and an extensive author and subject index aims to offer easy access to all the material included in both volumes.

The question of what environmental statistics is about is particularly important when it comes to the formulation of relevant research and training, whether in academia, agencies, or industries. This volume aims to give a new perception on the subject with some examples that are of concern and interest today. Environmental statistics is in a take-off stage both for reasons of societal challenge and statistical opportunity, and is demanding more and more from non-traditional and innovative statistical approaches. The chapters in this volume, which are specially prepared by several outstanding professionals involved in statistics and the environment, discuss the current state of the art in diverse areas of environmental statistics. The volume provides new perspectives and problems for future research, training, policy and regulation. It will be valuable to researchers, teachers, consultants and graduate students in statistics, environmental statistics, statistical ecology, and quantitative environmental sciences in academia, industries, governmental agencies, laboratories and libraries.

A principal feature of this book is the substantial care and attention devoted to explaining the basic ideas of the subject. Whenever a new theoretical concept is introduced it is carefully explained by reference to practical examples drawn mainly from the physical sciences. Subjects covered include: spectral analysis which is closely intertwined with the "time domain" approach, elementary notions of Hilbert Space Theory, basic probability theory, and practical analysis of time series data. The inclusion of material on "kalman filtering," state-space filtering," "non-linear models" and continuous time" models completes the impressive list of unique and detailed features which will give this book a prominent position among related literature. The first section -- Volume 1 -- deals with single (univariate) series, while the second -- Volume 2 -- treats the analysis of several (multivariate) series and the problems of prediction, forecasting and control.

The chapters in this monograph are contributions from the Advances in Quantum Monte Carlo symposium held at Pacifichem 2010, International Chemical Congress of Pacific Basin Societies. The symposium was dedicated to celebrate the career of James B. Anderson, a notable researcher in the field. Quantum Monte Carlo provides an ab initio solution to the Schroedinger equation by performing a random walk through configuration space in imaginary time. Benchmark calculations suggest that its most commonly-used variant, "fixed-node" diffusion Monte Carlo, estimates energies with an accuracy comparable to that of high-level coupled-cluster calculations. These two methods, each having advantages and disadvantages, are complementary "gold-standards" of quantum chemistry. There are challenges facing researchers in the field, several of which are addressed in the chapters in this monograph. These include improving the accuracy and precision of quantum Monte Carlo calculations; understanding the exchange nodes and utilizing the simulated electron distribution; extending the method to large and/or experimentally-challenging systems; and developing hybrid molecular mechanics/dynamics and Monte Carlo algorithms.

Multivariate Analysis deals with observations on more than one variable where there is some inherent interdependence between the variables. With several texts already available in this area, one may very well enquire of the authors as to the need for yet another book. Most of the available books fall into two categories, either theoretical or data analytic. The present book not only combines the two approaches but it also has been guided by the need to give suitable matter for the beginner as well as illustrating some deeper aspects of the subject for the research worker. Practical examples are kept to the forefront and, wherever feasible, each technique is motivated by such an example.

This worldwide best-selling business statistics text emphasizes applications over calculation. MANAGERIAL STATISTICS, 8e, International Editon demonstrates how vital statistical methods are for today's managers and economists--and teaches students how to apply these tools to real business problems. Through the author's unique three-step "ICI" approach to problem solving, students learn to IDENTIFY the correct statistical technique by focusing on the problem objective and data type, then COMPUTE the statistics (doing them by hand, using Excel (R), or using MINITAB (TM)), and ultimately INTERPRET results in the context of the problem. This approach enhances student comprehension and skills while offering you maximum flexibility. Incorporating various functional areas of business, data-driven examples, exercises, and cases demonstrate statistical applications used by marketing managers, financial analysts, accountants, economists, and others, giving students the hands-on practice they need, while sound pedagogical elements make the material accessible to undergrads. In addition, unique teaching and learning resources such as CengageNOW save time while giving you more control and better student outcomes. The eighth edition also includes Excel (R) 2007 and MINITAB 15 (TM) content.

The UK's most trusted A level Mathematics resources With over 900,000 copies sold (plus 1.3 million copies sold of the previous edition), Pearson's own resources for Pearson Edexcel are the market-leading and most trusted for AS and A level Mathematics. This book covers all the content needed for the optional Edexcel AS and A level Further Statistics 1 exams Enhanced focus on problem-solving and modelling, as well as supporting the large data set and calculators Packed with worked examples with guidance, lots of exam-style questions, practice papers, and plenty of mixed and review exercises Full worked solutions to every question available free and online for quick and easy access. Plus free additional online content with GeoGebra interactives and Casio calculator tutorials Practice books also available offering the most comprehensive and flexible AS/A level Maths practice with over 2000 extra questions Includes access to an online digital edition (valid for 3 years once activated) Pearson Edexcel AS and A level Further Mathematics Further Statistics 1 Textbook + e-book matches the Pearson Edexcel exam structure and is fully integrated with Pearson Edexcel's interactive scheme of work. All of the books in this series focus on problem-solving and modelling, as well as supporting the large data set and calculators. They are packed with worked examples with guidance, lots of exam-style questions, practice papers, and plenty of mixed and review exercises. There are full worked solutions to every question available free and online for quick and easy access. You will also have access to lots of free additional online content with GeoGebra interactives and Casio calculator tutorials. There are separate Pure and Applied textbooks for AS and A level Maths, and a textbook per option for AS and A level Further Maths. Practice books are also available offering the most comprehensive and flexible AS/A level Maths practice with over 2000 extra questions. Pearson's revision resources are the smart choice for those revising for Pearson Edexcel AS and A level Mathematics - there is a Revision Workbook for exam practice and a Revision Guide for classroom and independent study. Practice Papers Plus+ books contain additional full length practice papers, so you can practice answering questions by writing straight into the book and perfect your responses with targeted hints, guidance and support for every question, including fully worked solutions.

The UK's most trusted A level Mathematics resources With over 900,000 copies sold (plus 1.3 million copies sold of the previous edition), Pearson's own resources for Pearson Edexcel are the market-leading and most trusted for AS and A level Mathematics. Our A level Mathematics Statistics and Mechanics Year 1 Practice Book helps you get exam-ready with confidence and practice at the right pace. Coverage: the practice workbooks cover all Pure, Statistics and Mechanics topics Quantity: the most A level question practice available, with over 2,000 extra questions per book Practice at the right pace: start with the essentials, build your skills with various practice questions to make connections between topics, then apply this to exam-style questions at the end of each chapter Get exam-ready with confidence: differentiated questions including 'Bronze, Silver, Gold' in each chapter, and a mixed problem-solving section for each book, will guide and help you to develop the skills you need for your exams Designed to be used flexibly, the practice books are fully mapped to the scheme of work and textbooks so you can use them seamlessly in and out of the classroom and all year round. Use them lesson by lesson, topic by topic, for homework, revision and more - the choice is yours Great value practice materials that are cheaper than photocopying, saves more time than independently sourcing questions and answers, and are all in one place Pearson Edexcel AS and A level Mathematics Statistics and Mechanics Year 1/AS Practice Book matches the Pearson Edexcel exam structure and is fully integrated with Pearson Edexcel's interactive scheme of work. Practice books are also available offering the most comprehensive and flexible AS/A level Maths practice with over 2000 extra questions. Pearson's revision resources are the smart choice for those revising for Pearson Edexcel AS and A level Mathematics - there is a Revision Workbook for exam practice and a Revision Guide for classroom and independent study. Practice Papers Plus+ books contain additional full length practice papers, so you can practice answering questions by writing straight into the book and perfect your responses with targeted hints, guidance and support for every question, including fully worked solutions.

Developed for the new International A Level specification, these new resources are specifically designed for international students, with a strong focus on progression, recognition and transferable skills, allowing learning in a local context to a global standard. Recognised by universities worldwide and fully comparable to UK reformed GCE A levels. Supports a modular approach, in line with the specification. Appropriate international content puts learning in a real-world context, to a global standard, making it engaging and relevant for all learners. Reviewed by a language specialist to ensure materials are written in a clear and accessible style. The embedded transferable skills, needed for progression to higher education and employment, are signposted so students understand what skills they are developing and therefore go on to use these skills more effectively in the future. Exam practice provides opportunities to assess understanding and progress, so students can make the best progress they can.

Generalized Method of Moments (GMM) has become one of the main statistical tools for the analysis of economic and financial data. This book is the first to provide an intuitive introduction to the method combined with a unified treatment of GMM statistical theory and a survey of recent important developments in the field. Providing a comprehensive treatment of GMM estimation and inference, it is designed as a resource for both the theory and practice of GMM: it discusses and proves formally all the main statistical results, and illustrates all inference techniques using empirical examples in macroeconomics and finance. Building from the instrumental variables estimator in static linear models, it presents the asymptotic statistical theory of GMM in nonlinear dynamic models. Within this framework it covers classical results on estimation and inference techniques, such as the overidentifying restrictions test and tests of structural stability, and reviews the finite sample performance of these inference methods. And it discusses in detail recent developments on covariance matrix estimation, the impact of model misspecification, moment selection, the use of the bootstrap, and weak instrument asymptotics.

An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by way of case studies, giving readers the benefit of learning from real problems and real data. Aided by a diverse range of statistical methods and techniques, readers will move from simple problems to complex problems. Through these case studies, authors Adelchi Azzalini and Bruno Scarpa explain exactly how statistical methods work; rather than relying on the "push the button" philosophy, they demonstrate how to use statistical tools to find the best solution to any given problem. Case studies feature current topics highly relevant to data mining, such web page traffic; the segmentation of customers; selection of customers for direct mail commercial campaigns; fraud detection; and measurements of customer satisfaction. Appropriate for both advanced undergraduate and graduate students, this much-needed book will fill a gap between higher level books, which emphasize technical explanations, and lower level books, which assume no prior knowledge and do not explain the methodology behind the statistical operations.

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

This text introduces engineering students to probability theory and stochastic processes. Along with thorough mathematical development of the subject, the book presents intuitive explanations of key points in order to give students the insights they need to apply math to practical engineering problems. The first seven chapters contain the core material that is essential to any introductory course. In one-semester undergraduate courses, instructors can select material from the remaining chapters to meet their individual goals. Graduate courses can cover all chapters in one semester.

Developed for the new International A Level specification, these new resources are specifically designed for international students, with a strong focus on progression, recognition and transferable skills, allowing learning in a local context to a global standard. Recognised by universities worldwide and fully comparable to UK reformed GCE A levels. Supports a modular approach, in line with the specification. Appropriate international content puts learning in a real-world context, to a global standard, making it engaging and relevant for all learners. Reviewed by a language specialist to ensure materials are written in a clear and accessible style. The embedded transferable skills, needed for progression to higher education and employment, are signposted so students understand what skills they are developing and therefore go on to use these skills more effectively in the future. Exam practice provides opportunities to assess understanding and progress, so students can make the best progress they can.

* Starts from the basics, focusing less on proofs and the high-level math underlying regressions, and adopts an engaging tone to provide a text which is entirely accessible to students who don't have a stats background * New chapter on integrity and ethics in regression analysis * Each chapter offers boxed examples, stories, exercises and clear summaries, all of which are designed to support student learning * Optional appendix of statistical tools, providing a primer to readers who need it * Code in R and Stata, and data sets and exercises in Stata and CSV, to allow students to practice running their own regressions * Author-created videos on YouTube * PPT lecture slides and test bank for instructors