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The Practice of Econometric Theory
by Charles G. RenfroEconometric theory, as presented in textbooks and the econometric literature generally, is a somewhat disparate collection of findings. Its essential nature is to be a set of demonstrated results that increase over time, each logically based on a specific set of axioms or assumptions, yet at every moment, rather than a finished work, these inevitably form an incomplete body of knowledge. The practice of econometric theory consists of selecting from, applying, and evaluating this literature, so as to test its applicability and range. The creation, development, and use of computer software has led applied economic research into a new age. This book describes the history of econometric computation from 1950 to the present day, based upon an interactive survey involving the collaboration of the many econometricians who have designed and developed this software. It identifies each of the econometric software packages that are made available to and used by economists and econometricians worldwide.
The Practice of Statistics (Prep for the AP* Exam Guide)
by Michael LegacyPractice of Statistics: AP Exam Guide 3rd Edition by Michael Legacy
The Practice of Statistics: TI-83/84/89 Graphing Calculator Enhanced
by David S. Moore Daniel S. Yates Darren S. StarnesNIMAC-sourced textbook
The Practice of Statistics: TI-83/89 Graphing Calculator Enhanced (Prep for the AP Exam Guide)
by Larry PetersonBuilding on the "Prep for the AP Exam" feature on the Web, this study guide contains four full-length sample exams to help student refresh their skills and prepare for the actual AP Exam.
The Practice of Statistics
by Daren S. Starnes Josh Tabor Daniel S. Yates David S. MooreCombining a data analysis approach with the power of technology, innovative pedagogy, and a number of new features, this fifth edition has been updated to incorporate Learning Objectives in each section and link them to chapter reviews.
The Practice Of Statistics: Ti-83/84/89 Graphing Calculator Enhanced (Third Edition)
by Dan S. Yates David S. Moore Daren S. StarnesThe Practice of Statistics: TI-83/84/89 Graphing Calculator Enhanced (TPS), Third Edition, is an introductory text that focuses on data and statistical reasoning. It is intended for high school, college, and university students whose primary technological tool is the TI-83, TI-84, or TI-89 graphing calculator. <P><P> This book is based on the successful college textbooks The Basic Practice of Statistics (BPS) by David Moore and Introduction to the Practice of Statistics (IPS) by David Moore and George McCabe. <P>The Practice of Statistics was the first book written specifically for the College Board AP1 Statistics course. Statisticians have reached general consensus about the nature of a modern introductory statistics course. <P> A joint committee of the American Statistical Association and the Mathematical Association of America summarized this consensus as follows: Emphasize statistical thinking Present more data and concepts with less theory and fewer formulas Foster active learning
The Practice of Statistics: TI-83/89 Graphing Calculator Enhanced (2nd Edition)
by Daniel S. Yates David S. Moore Daren S. StarnesTailored to mirror the AP Statistics course, The Practice of Statistics became a classroom favorite. This edition incorporates a number of first-time features to help students prepare for the AP exam, plus more simulations and statistical thinking help, and instructions for the TI-89 graphic calculator.
The Practice Of Statistics
by Yates Daren S. Starnes Dan Yates David S. MooreCombining a data analysis approach with the power of technology, innovative pedagogy, and a number of new features, The Practice of Statistics is an impressively effective text for learning statistics. The fifth edition has been updated to incorporate Learning Objectives in each section and link them to chapter reviews.
The Practice of Statistics for AP
by Daren S. Starnes Daniel S. Yates David S. MooreCombining a data analysis approach with the power of technology, innovative pedagogy, and a number of new features, the fourth edition is an impressively effective text for learning statistics.
The Practice of Statistics for Business and Economics
by David S. Moore George P. Mccabe Bruce A. Craig Layth C. AlwanWith The Practice of Statistics for Business and Economics, instructors can help students develop a working knowledge of data production and interpretation in a business and economics context, giving them the practical tools they need to make data-informed, real-world business decisions from the first day of class. With its expanded, dedicated version of LaunchPad, the text more than ever is a seamlessly integrated print/online resource, putting powerful statistical tools and interactive learning features in students' hands.
The Practice of Statistics for the AP® Course
by Daren Starnes Josh TaborExperience the best: The Practice of Statistics is the ultimate choice for AP® Statistics.Authored by seasoned high school AP® Statistics educators, Daren Starnes and Josh Tabor, along with a team of experienced AP® teacher/leaders, the Seventh Edition of The Practice of Statistics brings a fresh perspective through 9 Units that align perfectly with the CED.Created to instill a deep understanding of the core principles of statistics and the problem-solving methods involved, TPS7 equips students with the essential statistical thinking skills necessary for future endeavors, careers, and everyday decision-making, while also ensuring success on the AP® Statistics Exam. With a multitude of worked examples and practice exercises strategically placed throughout, students have plenty of opportunities to strengthen their skills on a daily basis and prepare for the exam format.And thats not all - the renowned resource program now offers even greater support with the introduction of the new Achieve digital platform. The online homework program has been revamped to provide an extensive homework and assessment system, offering comprehensive support for daily assignments, quizzes, and tests. For students who may be struggling or seeking an extra challenge, the extensive video program is there to offer guidance. Meanwhile, teachers are backed by the most comprehensive Teachers Edition and resource program available. No matter if youre a first-time or experienced AP® Statistics teacher, this program is perfect for you.Better than ever: The Practice of Statistics is the most trusted program for AP® Statistics.
The Practice of Statistics for the AP® Exam
by Daren S. Starnes Josh TaborAlong came Dan Yates. His vision for such a text became reality with the publication of The Practice of Statistics (TPS) in 1998. Over a million students have used one of the first five editions of TPS for AP® Statistics! Dan also championed the importance of developing high-quality resources for AP® Statistics teachers, which were originally provided in a Teachers' Resource Binder. We stand on the shoulders of two giants in statistics education as we carry forward their visions in this and future editions. The Practice of Statistics has continued to evolve, thanks largely to the support of our longtime editor and team captain, Ann Heath. Her keen eye for design is evident throughout the pages of the student and teacher's editions. More importantly, Ann's ability to oversee all of the complex pieces of this project while maintaining a good sense of humor is legendary. Ann has continually challenged everyone involved with TPS to innovate in ways that benefit AP® Statistics students and teachers. She is a good friend and an inspirational leader.
The Practice of Statistics (For the AP Exam)
by Daren S. Starnes Dan Yates Josh Tabor David MooreCombining a data analysis approach with the power of technology, innovative pedagogy, and a number of new features, this fifth edition has been updated to incorporate Learning Objectives in each section and link them to chapter reviews.
The Practice of Statistics for the AP® Exam
by Daren Starnes Josh Tabor Ann Heath Donald Gecewicz Lumina DatamaticsNIMAC-sourced textbook
The Practice of Statistics in the Life Sciences
by Brigitte Baldi David S. MooreThis remarkably engaging textbook gives biology students an introduction to statistical practice all their own. It covers essential statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health. Based on David Moore's The Basic Practice of Statistics, PSLS mirrors that #1 bestseller's signature emphasis on statistical thinking, real data, and what statisticians actually do. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors.
Practice of Statistics in the Life Sciences, Digital Update
by Brigitte Baldi David S. MooreThe Practice of Statistics in the Life Sciences helps students understand how to apply essential statistical skills across life sciences including nursing, public health, and allied health.
The Practice of Statistics in the Life Sciences (Fourth Edition)
by Brigitte Baldi David S. MooreThis remarkably engaging textbook gives biology students an introduction to statistical practice all their own. It covers essential statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health. Based on David Moore's The Basic Practice of Statistics, PSLS mirrors that #1 bestseller's signature emphasis on statistical thinking, real data, and what statisticians actually do. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors.
Practice-Oriented Research in Tertiary Mathematics Education (Advances in Mathematics Education)
by Rolf Biehler Michael Liebendörfer Ghislaine Gueudet Chris Rasmussen Carl WinsløwThis edited volume presents a broad range of original practice-oriented research studies about tertiary mathematics education. These are based on current theoretical frameworks and on established and innovative empirical research methods. It provides a relevant overview of current research, along with being a valuable resource for researchers in tertiary mathematics education, including novices in the field. Its practice orientation research makes it attractive to university mathematics teachers interested in getting access to current ideas and results, including theory-based and empirically evaluated teaching and learning innovations.The content of the book is spread over 5 sections: The secondary-tertiary transition; University students' mathematical practices and mathematical inquiry; Research on teaching and curriculum design; University students’ mathematical inquiry and Mathematics for non-specialists.
Practicing R for Statistical Computing
by Muhammad Aslam Muhammad Imdad UllahThis book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation. It covers fundamental data structures such as vectors, matrices, arrays and lists, along with techniques for exploratory data analysis, data transformation and manipulation. The book explains basic statistical concepts and demonstrates their implementation using R, including descriptive statistics, graphical representation of data, probability, popular probability distributions and hypothesis testing. It also explores linear and non-linear modeling, model selection and diagnostic tools in R. The book also covers flow control and conditional calculations by using ‘‘if’’ conditions and loops and discusses useful functions and resources for further learning. It provides an extensive list of functions grouped according to statistics classification, which can be helpful for both statisticians and R programmers. The use of different graphic devices, high-level and low-level graphical functions and adjustment of parameters are also explained. Throughout the book, R commands, functions and objects are printed in a different font for easy identification. Common errors, warnings and mistakes in R are also discussed and classified with explanations on how to prevent them.
Practitioner’s Guide to Data Science (Chapman & Hall/CRC Data Science Series)
by Hui Lin Ming LiThis book aims to increase the visibility of data science in real-world, which differs from what you learn from a typical textbook. Many aspects of day-to-day data science work are almost absent from conventional statistics, machine learning, and data science curriculum. Yet these activities account for a considerable share of the time and effort for data professionals in the industry. Based on industry experience, this book outlines real-world scenarios and discusses pitfalls that data science practitioners should avoid. It also covers the big data cloud platform and the art of data science, such as soft skills. The authors use R as the primary tool and provide code for both R and Python. This book is for readers who want to explore possible career paths and eventually become data scientists. This book comprehensively introduces various data science fields, soft and programming skills in data science projects, and potential career paths. Traditional data-related practitioners such as statisticians, business analysts, and data analysts will find this book helpful in expanding their skills for future data science careers. Undergraduate and graduate students from analytics-related areas will find this book beneficial to learn real-world data science applications. Non-mathematical readers will appreciate the reproducibility of the companion R and python codes. Key Features: • It covers both technical and soft skills. • It has a chapter dedicated to the big data cloud environment. For industry applications, the practice of data science is often in such an environment. • It is hands-on. We provide the data and repeatable R and Python code in notebooks. Readers can repeat the analysis in the book using the data and code provided. We also suggest that readers modify the notebook to perform analyses with their data and problems, if possible. The best way to learn data science is to do it!
A Practitioner's Guide to State and Local Population Projections (The Springer Series on Demographic Methods and Population Analysis #37)
by David A. Swanson Stanley K. Smith Jeff TaymanThis book focuses on the methodology and analysis of state and local population projections. It describes the most commonly used data sources and application techniques for four types of projection methods: cohort-component, trend extrapolation, structural models, and microsimulation. It covers the components of population growth, sources of data, the formation of assumptions, the development of evaluation criteria, and the determinants of forecast accuracy. It considers the strengths and weaknesses of various projection methods and pays special attention to the unique problems that characterize small-area projections. The authors provide practical guidance to demographers, planners, market analysts, and others called on to construct state and local population projections. They use many examples and illustrations and present suggestions for dealing with special populations, unique circumstances, and inadequate or unreliable data. They describe techniques for controlling one set of projections to another, for interpolating between time points, for sub-dividing age groups, and for constructing projections of population-related variables (e. g. , school enrollment, households). They discuss the role of judgment and the importance of the political context in which projections are made. They emphasize the "utility" of projections, or their usefulness for decision making in a world of competing demands and limited resources. This comprehensive book will provide readers with an understanding not only of the mechanics of the most commonly used population projection methods, but also of the many complex issues affecting their construction, interpretation, evaluation, and use.
A Practitioner's Guide to Stochastic Frontier Analysis Using Stata
by Subal C. Kumbhakar Hung-Jen Wang Alan P. HorncastleStochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach. The authors explain in detail how to estimate production, cost, and profit efficiency and introduce the basic theory of each model in an accessible way, using empirical examples that demonstrate the interpretation and application of models. This book also provides computer code, allowing users to apply the models in their own work, and incorporates the most recent stochastic frontier models developed in academic literature. Such recent developments include models of heteroscedasticity and exogenous determinants of inefficiency, scaling models, panel models with time-varying inefficiency, growth models, and panel models that separate firm effects and persistent and transient inefficiency. Immensely helpful to applied researchers, this book bridges the chasm between theory and practice, expanding the range of applications in which production frontier analysis may be implemented.
The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions (Chapman And Hall/crc Machine Learning And Pattern Recognition Ser.)
by Marco Scutari Mauro MalvestioMachine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life. The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions discusses how modern software engineering practices are part of this revolution both conceptually and in practical applictions. Comprising a broad overview of how to design machine learning pipelines as well as the state-of-the-art tools we use to make them, this book provides a multi-disciplinary view of how traditional software engineering can be adapted to and integrated with the workflows of domain experts and probabilistic models. From choosing the right hardware to designing effective pipelines architectures and adopting software development best practices, this guide will appeal to machine learning and data science specialists, whilst also laying out key high-level principlesin a way that is approachable for students of computer science and aspiring programmers.
Pragmatics of Uncertainty (Chapman & Hall/CRC Texts in Statistical Science)
by Joseph B. KadaneA fair question to ask of an advocate of subjective Bayesianism (which the author is) is "how would you model uncertainty?" In this book, the author writes about how he has done it using real problems from the past, and offers additional comments about the context in which he was working.