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Author: Jon Curwin
Publisher: Cengage Learning
ISBN:
Category : Business & Economics
Languages : en
Pages : 370
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Book Description
Written specifically to support shorter courses in statistics and quantitative methods, this book provides revision for basic mathematical numerical skills, examines some simple statistical techniques, and introduces some basic quantitiative modelling techniques.
Author: Jon Curwin
Publisher: Cengage Learning
ISBN:
Category : Business & Economics
Languages : en
Pages : 370
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Book Description
Written specifically to support shorter courses in statistics and quantitative methods, this book provides revision for basic mathematical numerical skills, examines some simple statistical techniques, and introduces some basic quantitiative modelling techniques.
Author: Curwin Slater Staff
Publisher:
ISBN: 9781844804856
Category :
Languages : en
Pages :
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Book Description
Author: Daniela Aidley
Publisher: Bloomsbury Publishing
ISBN: 1137487224
Category : Psychology
Languages : en
Pages : 360
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Book Description
This exciting new core textbook offers a clear and practical introduction to quantitative methods, taking a project-based approach. The author's extensive knowledge and straightforward writing style ensure that students are steered through the process step-by-step, from developing research questions and preparing data for analysis, to explaining how to present data in appropriate formats, avoid bias, and write up results and reports. Featuring a comprehensive pedagogical framework and companion website, readers are encouraged to follow practice analyses as they go, with examples given in both SPSS and Excel, and templates are provided for students' own research. In addition to covering the research project, chapters also cover the essential mathematical and statistical analyses that are a logical consequence of posing a quantitative research methods question. This is the perfect text for all social science students studying introductory modules on quantitative methods, research methods or statistics at undergraduate or postgraduate level. It also functions as an effective guide for undergraduate and postgraduate students faced with an independent research project.
Author: Catherine Pope
Publisher: John Wiley & Sons
ISBN: 1119410835
Category : Medical
Languages : en
Pages : 278
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Book Description
Provides the essential information that health care researchers and health professionals need to understand the basics of qualitative research Now in its fourth edition, this concise, accessible, and authoritative introduction to conducting and interpreting qualitative research in the health care field has been fully revised and updated. Continuing to introduce the core qualitative methods for data collection and analysis, this new edition also features chapters covering newer methods which are becoming more widely used in the health research field; examining the role of theory, the analysis of virtual and digital data, and advances in participatory approaches to research. Qualitative Research in Health Care, 4th Edition looks at the interface between qualitative and quantitative research in primary mixed method studies, case study research, and secondary analysis and evidence synthesis. The book further offers chapters covering: different research designs, ethical issues in qualitative research; interview, focus group and observational methods; and documentary and conversation analysis. A succinct, and practical guide quickly conveying the essentials of qualitative research Updated with chapters on new and increasingly used methods of data collection including digital and web research Features new examples and up-to-date references and further reading The fourth edition of Qualitative Research in Health Care is relevant to health care professionals, researchers and students in health and related disciplines.
Author: Bharat Kolluri
Publisher: John Wiley & Sons
ISBN: 1119220971
Category : Mathematics
Languages : en
Pages : 314
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Book Description
A well-balanced and accessible introduction to the elementary quantitative methods and Microsoft® Office Excel® applications used to guide business decision making Featuring quantitative techniques essential for modeling modern business situations, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® provides guidance to assessing real-world data sets using Excel. The book presents a balanced approach to the mathematical tools and techniques with applications used in the areas of business, finance, economics, marketing, and operations. The authors begin by establishing a solid foundation of basic mathematics and statistics before moving on to more advanced concepts. The first part of the book starts by developing basic quantitative techniques such as arithmetic operations, functions and graphs, and elementary differentiations (rates of change), and integration. After a review of these techniques, the second part details both linear and nonlinear models of business activity. Extensively classroom-tested, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® also includes: Numerous examples and practice problems that emphasize real-world business quantitative techniques and applications Excel-based computer software routines that explore calculations for an assortment of tasks, including graphing, formula usage, solving equations, and data analysis End-of-chapter sections detailing the Excel applications and techniques used to address data and solutions using large data sets A companion website that includes chapter summaries, Excel data sets, sample exams and quizzes, lecture slides, and an Instructors’ Solutions Manual Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® is an excellent textbook for undergraduate-level courses on quantitative methods in business, economics, finance, marketing, operations, and statistics. The book is also an ideal reference for readers with little or no quantitative background who require a better understanding of basic mathematical and statistical concepts used in economics and business. Bharat Kolluri, Ph.D., is Professor of Economics in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include econometrics, business statistics, quantitative decision making, applied macroeconomics, applied microeconomics, and corporate finance. Michael J. Panik, Ph.D., is Professor Emeritus in the Department of Economics, Finance, and Insurance at the University of Hartford. He has served as a consultant to the Connecticut Department of Motor Vehicles as well as to a variety of health care organizations. In addition, Dr. Panik is the author of numerous books, including Growth Curve Modeling: Theory and Applications and Statistical Inference: A Short Course, both published by Wiley. Rao N. Singamsetti, Ph.D., is Associate Professor in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include the status of war on poverty in the United States since the 1960s and forecasting foreign exchange rates using econometric methods.
Author: John I. Gallin
Publisher: Elsevier
ISBN: 0080489567
Category : Science
Languages : en
Pages : 447
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Book Description
The second edition of this innovative work again provides a unique perspective on the clinical discovery process by providing input from experts within the NIH on the principles and practice of clinical research. Molecular medicine, genomics, and proteomics have opened vast opportunities for translation of basic science observations to the bedside through clinical research. As an introductory reference it gives clinical investigators in all fields an awareness of the tools required to ensure research protocols are well designed and comply with the rigorous regulatory requirements necessary to maximize the safety of research subjects. Complete with sections on the history of clinical research and ethics, copious figures and charts, and sample documents it serves as an excellent companion text for any course on clinical research and as a must-have reference for seasoned researchers. *Incorporates new chapters on Managing Conflicts of Interest in Human Subjects Research, Clinical Research from the Patient's Perspective, The Clinical Researcher and the Media, Data Management in Clinical Research, Evaluation of a Protocol Budget, Clinical Research from the Industry Perspective, and Genetics in Clinical Research *Addresses the vast opportunities for translation of basic science observations to the bedside through clinical research*Delves into data management and addresses how to collect data and use it for discovery*Contains valuable, up-to-date information on how to obtain funding from the federal government
Author: Kosuke Imai
Publisher: Princeton University Press
ISBN: 0691191093
Category : Political Science
Languages : en
Pages : 464
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Book Description
"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--
Author: Konrad Hugo Jarausch
Publisher: UNC Press Books
ISBN: 9780807843093
Category : History
Languages : en
Pages : 272
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Book Description
The pioneering texts in quantitative history were written over two decades ago, but as a command of methodological context, computer experience, and statistical literacy have become increasingly important to the study of history, the need for an introduct
Author: Simon Walkowiak
Publisher: Packt Publishing Ltd
ISBN: 1786463725
Category : Computers
Languages : en
Pages : 498
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Book Description
Utilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market Who This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R. What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities Deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner Apply the R language to real-world Big Data problems on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platform In Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O. Style and approach This book will serve as a practical guide to tackling Big Data problems using R programming language and its statistical environment. Each section of the book will present you with concise and easy-to-follow steps on how to process, transform and analyse large data sets.
Author: Joseph Lee Rodgers
Publisher: Routledge
ISBN: 0429810210
Category : Education
Languages : en
Pages : 296
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Book Description
This work, which provides a guide for revising and expanding statistical and quantitative methods pedagogy, is useful for novice and seasoned instructors at both undergraduate and graduate levels, inspiring them to use transformative approaches to train students as future researchers. Is it time for a radical revision in our pedagogical orientation? How are we currently teaching introductory statistics and quantitative methods, and how should we teach them? What innovations are used, what is in development? This ground-breaking edited volume addresses these questions and more, providing cutting-edge guidance from highly accomplished teachers. Many current textbooks and syllabi differ in only superficial ways from those used 50 years ago, yet the field of quantitative methods—and its relationship to the research enterprise—has expanded in many important ways. A philosophical axiom underlying this book is that introductory teaching should prepare students to potentially enter more advanced quantitative methods training and ultimately to become accomplished researchers. The reader is introduced to classroom innovation, and to both pragmatic and philosophical challenges to the status quo, motivating a broad revolution in how introductory statistics and quantitative methods are taught. Designed to update and renovate statistical pedagogy, this material will stimulate students, new instructors, and experienced teachers.