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Demonstrate how statistical methods are vital for today's managers and economists as you teach students how to apply these tools to real business problems with the 11th edition of Statistics for Management and Economics.
This best-selling business and economic statistics text emphasizes applications over calculations using a unique three-step "ICI" approach to problem solving. Students IDENTIFY the correct statistical technique by focusing on the problem objective and data type; then COMPUTE the statistics (by hand, using ExcelŽ 2016, or using XLSTAT Excel add-in); and ultimately INTERPRET results in the context of the problem.
Readers examine functional areas of business as data-driven examples, more than 2400 exercises, and 32 cases demonstrate how marketing managers, financial analysts, accountants, and economists use statistical applications. Many exercises feature returns on 40 stocks. Students can download 1100 data sets, online appendixes and Data Analysis Plus from the book’s website.
Aplia FOR INTRODUCTORY BUSINESS STATISTICS HELPS STUDENTS STAY ON TOP OF COURSEWORK WITH REGULARLY SCHEDULED ASSIGNMENTS. Developed by teachers and used by more than 1,000,000 students, Aplia features interactive assignments that connect concepts to the real world. Auto-assigned, auto-graded homework holds students accountable for the material before they come to class. Immediate, detailed explanations for every answer enhance comprehension of foundational knowledge and statistical concepts. Gradebook Analytics allow you to monitor performance on a student-by-student basis.
EMPHASIS ON IDENTIFICATION AND INTERPRETATION PROVIDES STUDENTS WITH PRACTICAL SKILLS. With this book’s emphasis on applications rather than calculations, your student master and practice skills they can apply to real-world problems, whether you choose to use manual or computer calculations.
STUDENTS HAVE THE OPPORTUNITY TO CONVERT REAL DATA INTO INFORMATION. This book gives you flexibility, with the optional use of computer software, to teach your students how to work with larger data sets and more realistic exercises and examples....
Essential Mathematics for Economics and Business is established as one of the leading introductory textbooks on mathematics for students of business and economics. Combining a user friendly approach to mathematics with practical applications to the subjects, the text provides students with a clear and comprehensible guide to mathematics. The fundamental mathematical concepts are explained in a simple and accessible style, using a wide selection of worked examples, progress exercises and real world applications. New to this Edition * Fully updated text with revised worked examples and updated material on Excel and Powerpoint * New exercises in mathematics and its applications to give further clarity and practice opportunities * Fully updated online material including animations and a new test bank * The fourth edition is supported by a companion website at www.wiley.com/college/bradley, which contains: Animations of selected worked examples providing students with a new way of understanding the problems Access to the Maple T.A. test bank, which features over 500 algorithmic questions Further learning material, applications, exercises and solutions. * Problems in context studies, which present the mathematics in a business or economics framework. * Updated PowerPoint slides, Excel problems and solutions. "The text is aimed at providing an introductory-level exposition of mathematical methods for economics and business students. In terms of level, pace, complexity of examples and user-friendly style the text is excellent - it genuinely recognises and meets the needs of students with minimal maths background." Colin Glass, Emeritus Professor, University of Ulster "One of the major strengths of this book is the range of exercises in both drill and applications. Also the 'worked examples' are excellent; they provide examples of the use of mathematics to realistic problems and are easy to follow." Donal Hurley, formerly of University College Cork "The most comprehensive reader in this topic yet, this book is an essential aid to the avid economist who loathes mathematics!" Amazon.co.uk
This book shows how our lives are shaped not only by the choices we make, but by the choices we have. From dating, school and university applications to the job market, understand the most important decisions you'll ever make with insights from a Nobel Prize-winner. Who Gets What and Why is a piquantly written, mind-expanding exploration of the markets that matter most to many of us. If you've ever sought a job or hired someone, applied to university or guided your child into a good school, asked someone out on a date or been asked out, you have participated in a matching market. They are everywhere around us and account for some of the biggest technological successes of the decade, like Uber and Airbnb. Matching markets can even be the gatekeeper of life itself, guiding how desperately ill patients receive scarce organs for transplants. Alvin E. Roth shared the 2012 Nobel Prize in economics for his pioneering research into market design - the principles that govern all kinds of markets where money isn't the only factor in determining who gets what. His book reveals what factors make these markets work well - or badly - and shows us all how to recognise a good match and make smarter, more confident decisions.
Discover how empirical researchers today actually consider and apply econometric methods with the practical approach in Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 6E. Unlike traditional texts, this book uniquely demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions in business, policy evaluation, and forecasting. INTRODUCTORY ECONOMETRICS is organized around the type of data being analyzed with a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, the text incorporates more than 100 intriguing data sets, available in six formats. Updates introduce the latest emerging developments in the field. Gain a full understanding of the impact of econometrics in practice today with the insights and applications found only in INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 6E.
This book examines whether continuous-time models in frictionless financial economies can be well approximated by discrete-time models. It specifically looks to answer the question: in what sense and to what extent does the famous Black-Scholes-Merton (BSM) continuous-time model of financial markets idealize more realistic discrete-time models of those markets? While it is well known that the BSM model is an idealization of discrete-time economies where the stock price process is driven by a binomial random walk, it is less known that the BSM model idealizes discrete-time economies whose stock price process is driven by more general random walks. Starting with the basic foundations of discrete-time and continuous-time models, David M. Kreps takes the reader through to this important insight with the goal of lowering the entry barrier for many mainstream financial economists, thus bringing less-technical readers to a better understanding of the connections between BSM and nearby discrete-economies.
Interest in nonparametric methodology has grown considerably over the past few decades, stemming in part from vast improvements in computer hardware and the availability of new software that allows practitioners to take full advantage of these numerically intensive methods. This book is written for advanced undergraduate students, intermediate graduate students, and faculty, and provides a complete teaching and learning course at a more accessible level of theoretical rigor than Racine's earlier book co-authored with Qi Li, Nonparametric Econometrics: Theory and Practice (2007). The open source R platform for statistical computing and graphics is used throughout in conjunction with the R package np. Recent developments in reproducible research is emphasized throughout with appendices devoted to helping the reader get up to speed with R, R Markdown, TeX and Git.
A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python software guides.
Gain an understanding of how econometrics can answer today's questions in business, policy evaluation and forecasting with Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 7E. Unlike traditional texts, this book's practical, yet professional, approach demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions across a variety of disciplines. The author has organized the book's presentation around the type of data being analyzed with a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, the text incorporates more than 100 data sets in different formats. Updates introduce the latest developments in the field, including the recent advances in the so-called "causal effects" or "treatment effects," to provide a complete understanding of the impact and importance of econometrics today.
Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detailed solutions to those questions. This second edition adds extensive coverage of models popular in finance and macroeconomics, including state space and unobserved components models, stochastic volatility models, ARCH, GARCH, and vector autoregressive models. The authors have also added many new exercises related to Gibbs sampling and Markov Chain Monte Carlo (MCMC) methods. The text includes regression-based and hierarchical specifications, models based upon latent variable representations, and mixture and time series specifications. MCMC methods are discussed and illustrated in detail - from introductory applications to those at the current research frontier - and MATLAB (R) computer programs are provided on the website accompanying the text. Suitable for graduate study in economics, the text should also be of interest to students studying statistics, finance, marketing, and agricultural economics.
This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overview for students.
For courses in Introductory Econometrics Engaging applications bring the theory and practice of modern econometrics to life Ensure students grasp the relevance of econometrics with Introduction to Econometrics-the text that connects modern theory and practice with motivating, engaging applications. The Third Edition Update maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. This program provides a better teaching and learning experience-for you and your students. Here's how: Keeping it current with new and updated discussions on topics of particular interest to today's students. Presenting consistency through theory that matches application. Offering a full array of pedagogical features. MyEconLab (R) is not included. Students, if MyEconLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. MyEconLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MyEconLab is an online homework, tutorial, and assessment product designed to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.
Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader's understanding of the methods in question and their assumptions. Empirical examples are provided for illustration.
The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes. In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? "Mostly Harmless Econometrics" shows how the basic tools of applied econometrics allow the data to speak.
In addition to econometric essentials, "Mostly Harmless Econometrics" covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications"
High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the first to integrate theory, key tools, and modern applications of high-dimensional probability. Concentration inequalities form the core, and it covers both classical results such as Hoeffding's and Chernoff's inequalities and modern developments such as the matrix Bernstein's inequality. It then introduces the powerful methods based on stochastic processes, including such tools as Slepian's, Sudakov's, and Dudley's inequalities, as well as generic chaining and bounds based on VC dimension. A broad range of illustrations is embedded throughout, including classical and modern results for covariance estimation, clustering, networks, semidefinite programming, coding, dimension reduction, matrix completion, machine learning, compressed sensing, and sparse regression.
This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance. The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving real-world problems, with lecture slides, additional computational exercises in Julia and MATLAB (R), and data sets accompanying the book online. Suitable for both one-semester and one-quarter courses, as well as self-study, this self-contained text provides beginning students with the foundation they need to progress to more advanced study.
Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. * Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods* Approaches forecasting from a decision theoretic and estimation perspective* Covers Bayesian modeling, including methods for generating density forecasts* Discusses model selection methods as well as forecast combinations* Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility* Features numerous empirical examples* Examines the latest advances in forecast evaluation* Essential for practitioners and students alike
Applied econometrics, known to aficionados as 'metrics, is the original data science. 'Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. Through accessible discussion and with a dose of kung fu-themed humor, Mastering 'Metrics presents the essential tools of econometric research and demonstrates why econometrics is exciting and useful. The five most valuable econometric methods, or what the authors call the Furious Five--random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences--are illustrated through well-crafted real-world examples (vetted for awesomeness by Kung Fu Panda's Jade Palace). Does health insurance make you healthier? Randomized experiments provide answers. Are expensive private colleges and selective public high schools better than more pedestrian institutions? Regression analysis and a regression discontinuity design reveal the surprising truth. When private banks teeter, and depositors take their money and run, should central banks step in to save them? Differences-in-differences analysis of a Depression-era banking crisis offers a response. Could arresting O. J. Simpson have saved his ex-wife's life? Instrumental variables methods instruct law enforcement authorities in how best to respond to domestic abuse. Wielding econometric tools with skill and confidence, Mastering 'Metrics uses data and statistics to illuminate the path from cause to effect. * Shows why econometrics is important* Explains econometric research through humorous and accessible discussion* Outlines empirical methods central to modern econometric practice* Works through interesting and relevant real-world examples
Volatility ranks among the most active and successful areas of research in econometrics and empirical asset pricing finance over the past three decades. This two-volume collection of papers comprises some of the most influential published works from this burgeoning literature, both classic and contemporary. Topics covered include GARCH, stochastic and multivariate volatility models as well as forecasting, evaluation and high-frequency data. Together with an original introduction by the editors, this definitive compilation presents the most important milestones and contributions that helped pave the way to today's understanding of volatility.
Over the past two decades, experimental economics has moved from a fringe activity to become a standard tool for empirical research. With experimental economics now regarded as part of the basic tool-kit for applied economics, this book demonstrates how controlled experiments can be a useful in providing evidence relevant to economic research. Professors Jacquemet and L'Haridon take the standard model in applied econometrics as a basis to the methodology of controlled experiments. Methodological discussions are illustrated with standard experimental results. This book provides future experimental practitioners with the means to construct experiments that fit their research question, and new comers with an understanding of the strengths and weaknesses of controlled experiments. Graduate students and academic researchers working in the field of experimental economics will be able to learn how to undertake, understand and criticise empirical research based on lab experiments, and refer to specific experiments, results or designs completed with case study applications.
Probability comes of age with this, the first dictionary of probability and its applications in English, which supplies a guide to the concepts and vocabulary of this rapidly expanding field. Besides the basic theory of probability and random processes, applications covered here include financial and insurance mathematics, operations research (including queueing, reliability, and inventories), decision and game theory, optimization, time series, networks, and communication theory, as well as classic problems and paradoxes. The dictionary is reliable, stable, concise, and cohesive. Each entry provides a rigorous definition, a sketch of the context, and a reference pointing the reader to the wider literature. Judicious use of figures makes complex concepts easier to follow without oversimplifying. As the only dictionary on the market, this will be a guiding reference for all those working in, or learning, probability together with its applications.
This research collection offers a 34-article tour of recent advances and the current state of 5 important and booming areas of empirical methodology: Bayesian methods; modelling of temporal duration, dependence, and dynamics; network-analytic methodology; text, classification, and big-data analytic methods; methods for nonparametric and design-based causal inference. These prominent articles, written by leading scholars, break new ground and provide definitive statements of the current best practices in those respective areas. Together they describe the cutting-edge profile of modern empirical methodology for applied empirical analysis in political science. This is an essential resource for those studying and researching political methodology.
Methods and perspectives to model and measure productivity and efficiency have made a number of important advances in the last decade. Using the standard and innovative formulations of the theory and practice of efficiency and productivity measurement, Robin C. Sickles and Valentin Zelenyuk provide a comprehensive approach to productivity and efficiency analysis, covering its theoretical underpinnings and its empirical implementation, paying particular attention to the implications of neoclassical economic theory. A distinct feature of the book is that it presents a wide array of theoretical and empirical methods utilized by researchers and practitioners who study productivity issues. An accompanying website includes methods, programming codes that can be used with widely available software like MATLAB (R) and R, and test data for many of the productivity and efficiency estimators discussed in the book. It will be valuable to upper-level undergraduates, graduate students, and professionals.
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