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Probability & Statistics
|Design and Analysis of Experiments
Lowest new price: $149.69
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List price: $147.70
Author: Douglas C. Montgomery
Brand: Douglas C Montgomery
The eighth edition of this best selling text continues to help senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems.
The eighth edition of Design and Analysis of Experiments maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book.
Continuing to place a strong focus on the use of the computer, this edition includes software examples taken from the four most dominant programs in the field: Design-Expert, Minitab, JMP, and SAS.
- Design and Analysis of Experiments
|Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer Series in Statistics)
Lowest new price: $49.15
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List price: $89.99
Author: Frank E. Harrell Jr.
This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modelling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasises problem solving strategies that address the many issues arising when developing multi-variable models using real data and not standard textbook examples.
Regression Modelling Strategies presents full-scale case studies of non-trivial data-sets instead of over-simplified illustrations of each method. These case studies use freely available R functions that make the multiple imputation, model building, validation and interpretation tasks described in the book relatively easy to do. Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model. A new emphasis is given to the robust analysis of continuous dependent variables using ordinal regression.As in the first edition, this text is intended for Masters' or PhD. level graduate students who have had a general introductory probability and statistics course and who are well versed in ordinary multiple regression and intermediate algebra. The book will also serve as a reference for data analysts and statistical methodologists, as it contains an up-to-date survey and bibliography of modern statistical modelling techniques.
|Fundamentals of Clinical Trials
Lowest new price: $42.13
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List price: $79.99
Author: Lawrence M. Friedman
This is the fifth edition of a very successful textbook on clinical trials methodology, written by recognized leaders who have long and extensive experience in all areas of clinical trials. The three authors of the first four editions have been joined by two others who add great expertise. A chapter on regulatory issues has been included and the chapter on data monitoring has been split into two and expanded. Many contemporary clinical trial examples have been added. There is much new material on adverse events, adherence, issues in analysis, electronic data, data sharing and international trials.
This book is intended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must critically evaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The authors use numerous examples of published clinical trials to illustrate the fundamentals.
The text is organized sequentially from defining the question to trial closeout. One chapter is devoted to each of the critical areas to aid the clinical trial researcher. These areas include pre-specifying the scientific questions to be tested and appropriate outcome measures, determining the organizational structure, estimating an adequate sample size, specifying the randomization procedure, implementing the intervention and visit schedules for participant evaluation, establishing an interim data and safety monitoring plan, detailing the final analysis plan and reporting the trial results according to the pre-specified objectives.
Although a basic introductory statistics course is helpful in maximizing the benefit of this book, a researcher or practitioner with limited statistical background would still find most if not all the chapters understandable and helpful. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this text useful.
|The Basic Practice of Statistics
Lowest new price: $64.85
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List price: $220.99
Author: David S. Moore
David Moore’s data analysis (conceptual) approach, which revolutionized the introductory statistics textbook, moves students away from formulas and number-crunching, focusing instead on how working statisticians in a variety of fields collect and analyze data, and use the results to tackle real-world problems.
The clear, direct way of emphasizing the course’s relevance and confronting students’ math anxieties is at the heart of the bestselling The Basic Practice of Statistics (BPS). It is also the ideal approach for taking full advantage of the powerful statistical tools and interactive learning features in this new edition’s text/media package. Now more than ever, BPS is ready to help students move from reading about statistical practice to practicing statistics themselves.
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|Introduction to Probability (Chapman & Hall/CRC Texts in Statistical Science)
Lowest new price: $64.04
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Author: Joseph K. Blitzstein
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version.
The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces.
The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.
- Introduction to Probability, Statistics, and Random Processes
- Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman & Hall/CRC Texts in Statistical Science)
- Probability: For the Enthusiastic Beginner
- Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
- Student's Solutions Guide for Introduction to Probability, Statistics, and Random Processes
- An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
- Introduction to Linear Algebra, Fifth Edition
- Linear Algebra with Applications, 5th Edition
- All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)
- Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan
|Applied Statistics: From Bivariate Through Multivariate Techniques
Lowest new price: $132.00
Lowest used price: $105.00
List price: $154.00
Author: Rebecca M. Warner
Brand: Rebecca M Warner
Rebecca M. Warner′s Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.
- Applied Statistics From Bivariate Through Multivariate Techniques
|A Gentle Introduction to Stata, Fifth Edition
Lowest new price: $59.36
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List price: $83.95
Author: Alan C. Acock
Alan C. Acock's A Gentle Introduction to Stata, Fifth Edition,
is aimed at new Stata users who want to become proficient in Stata.
After reading this introductory text, new users will be able not only
to use Stata well but also to learn new aspects of Stata.
Acock assumes that the user is not familiar with any statistical
software. This assumption of a blank slate is central to the structure
and contents of the book. Acock starts with the basics; for example,
the portion of the book that deals with data management begins with a
careful and detailed example of turning survey data on paper into a
Stata-ready dataset on the computer. When explaining how to go about
basic exploratory statistical procedures, Acock includes notes that
will help the reader develop good work habits. This mixture of
explaining good Stata habits and good statistical habits continues
throughout the book.
Acock is quite careful to teach the reader all aspects of using Stata.
He covers data management, good work habits (including the use of
basic do-files), basic exploratory statistics (including graphical
displays), and analyses using the standard array of basic statistical
tools (correlation, linear and logistic regression, and parametric and
nonparametric tests of location and dispersion). He also successfully
introduces some more advanced topics such as multiple imputation and
structural equation modeling in a very approachable manner. Acock
teaches Stata commands by using the menus and dialog boxes while still
stressing the value of do-files. In this way, he ensures that all
types of users can build good work habits. Each chapter has exercises
that the motivated reader can use to reinforce the material.
The tone of the book is friendly and conversational without ever being
glib or condescending. Important asides and notes about terminology
are set off in boxes, which makes the text easy to read without any
convoluted twists or forward-referencing. Rather than splitting topics
by their Stata implementation, Acock arranges the topics as they would
appear in a basic statistics textbook; graphics and postestimation are
woven into the material in a natural fashion. Real datasets, such as
the General Social Surveys from 2002 and 2006, are used
throughout the book.
The focus of the book is especially helpful for those in the
behavioral and social sciences because the presentation of basic
statistical modeling is supplemented with discussions of effect sizes
and standardized coefficients. Various selection criteria, such as
semipartial correlations, are discussed for model selection. Acock
also covers a variety of commands available for evaluating reliability
and validity of measurements.
The fifth edition of the book includes two new chapters that cover
multilevel modeling and item response theory (IRT) models. The
multilevel modeling chapter demonstrates how to fit linear multilevel
models using the mixed command. Acock discusses models with
both random intercepts and random coefficients, and he provides a
variety of examples that apply these models to longitudinal data. The
IRT chapter introduces the use of IRT models for evaluating a set of
items designed to measure a specific trait such as an attitude, value,
or a belief. Acock shows how to use the irt suite of commands,
which are new in Stata 14, to fit IRT models and to graph the results.
In addition, he presents a measure of reliability that can be computed
when using IRT.
|Trump Never Give Up: How I Turned My Biggest Challenges into Success
Lowest new price: $11.52
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List price: $19.95
Author: Donald J. Trump
Brand: Donald J Trump
In Never Give Up, Donald Trump tells the dramatic stories of his biggest challenges, lowest moments, and worst mistakes—and how he uses tenacity and creativity to turn defeat into victory. Each chapter includes an inspiring story from Trump’s career and concludes with expert commentary and coaching from adversity researcher and author Paul Stoltz. Inspirational and intelligent, Never Give Up will help you deal with your own personal challenges, failures, and weaknesses.
- Trump Never Give Up How I Turned My Biggest Challenges into Success
|Essentials of Statistics (5th Edition)
Lowest new price: $78.00
Lowest used price: $25.65
List price: $177.80
Author: Mario F. Triola
Note: You are purchasing a standalone product; MyStatLab does not come packaged with this content. If you would like to purchase both the physical text and MyStatLab, search for ISBN-10: 0133864960/ISBN-13: 9780133864960 . That package includes ISBN-10: 0321847997/ISBN-13:9780321847997, ISBN-10: 032184839X/ISBN-13:9780321848390 andISBN-10: 0321924592/ISBN-13: 9780321924599.
MyStatLab is not a self-paced technology and should only be purchased when required by an instructor.
From SAT scores to job search methods, statistics influences and shapes the world around us. Marty Triola’s text continues to be the bestseller because it helps students understand the relationship between statistics and the world, bringing life to the theory and methods. Essentials of Statistics raises the bar with every edition by incorporating an unprecedented amount of real and interesting data that will help instructors connect with students today, and help them connect statistics to their daily lives. The Fifth Edition contains more than 1,800 exercises, 89% of which use real data and 85% of which are new. Hundreds of examples are included, 91% of which use real data and 84% of which are new. New coverage of Ethics in Statistics highlights new guidelines that have been established in the industry.
|Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
Lowest new price: $81.24
Lowest used price: $69.14
List price: $135.00
Author: Galit Shmueli
Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration
Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities.
This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes:
• Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government
• Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students
• More than a dozen case studies demonstrating applications for the data mining techniques described
• End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented
• A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions
Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.
“ This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.”
Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 publications including books.
Peter C. Bruce is President and Founder of the Institute for Statistics Education at Statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective (Wiley) and co-author of Practical Statistics for Data Scientists: 50 Essential Concepts (O’Reilly).
Inbal Yahav, PhD, is Professor at the Graduate School of Business Administration at Bar-Ilan University, Israel. She teaches courses in social network analysis, advanced research methods, and software quality assurance. Dr. Yahav received her PhD in Operations Research and Data Mining from the University of Maryland, College Park.
Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad, for 15 years.
Kenneth C. Lichtendahl, Jr., PhD, is Associate Professor at the University of Virginia. He is the Eleanor F. and Phillip G. Rust Professor of Business Administration and teaches MBA courses in decision analysis, data analysis and optimization, and managerial quantitative analysis. He also teaches executive education courses in strategic analysis and decision-making, and managing the corporate aviation function.
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