Principles Of Applied Statistics And Information Management
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Principles of Applied Statistics by M. C. Fleming Pdf
Principles of Applied Statistics provides the reader with a comprehensive overview of statistical techniques and their applications. Explaining the methods of information management with reference to computer packages including MINITAB, this text will develop the skills of the manager seeking to use information accurately and effectively.
Principles of Applied Statistics by D. R. Cox,Christl A. Donnelly Pdf
Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.
Modern Applied Statistics with S-Plus by W.N. Venables,B.D. Ripley Pdf
A guide to using S-Plus to perform statistical analyses, serving as both an introduction to the use of S-Plus and as a course in modern statistical methods. The experienced authors show how to use S-Plus as a powerful and graphical system, with the emphasis on presenting practical problems and full analyses of real data sets throughout. A basic grounding in statistics is assumed, making this book suitable for would-be users of S-Plus, as well as students and researchers using statistics.
Data Mining: Concepts and Techniques by Jiawei Han,Micheline Kamber,Jian Pei Pdf
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Applied Statistics for Social and Management Sciences by Abdul Quader Miah Pdf
This book addresses the application of statistical techniques and methods across a wide range of disciplines. While its main focus is on the application of statistical methods, theoretical aspects are also provided as fundamental background information. It offers a systematic interpretation of results often discovered in general descriptions of methods and techniques such as linear and non-linear regression. SPSS is also used in all the application aspects. The presentation of data in the form of tables and graphs throughout the book not only guides users, but also explains the statistical application and assists readers in interpreting important features. The analysis of statistical data is presented consistently throughout the text. Academic researchers, practitioners and other users who work with statistical data will benefit from reading Applied Statistics for Social and Management Sciences.
Author : Axel Schniederjürgen Publisher : Walter de Gruyter Page : 561 pages File Size : 49,5 Mb Release : 2008-12-19 Category : Language Arts & Disciplines ISBN : 9783598440298
World Guide to Library, Archive and Information Science Education by Axel Schniederjürgen Pdf
This directory lists education institutions world-wide where professional education and training programmes in the field of library, archive and information science are carried out at a tertiary level of education or higher. More than ten years after the publication of the last edition, this up-to-date reference source includes more than 900 universities and other institutions, and more than 1.500 relevant programmes. Entries provide contact information as well as details such as statistical information, tuition fees, admission requirements, programmes' contents.
Applied Statistics in the Pharmaceutical Industry by Steven P. Millard,Andreas Krause Pdf
Providing a general guide to statistical methods used in the pharmaceutical industry, and illustrating how to use S-PLUS to implement these methods, the book explains why S-PLUS is a useful software package and discusses the results and implications of each particular application. It is targeted at graduates in biostatistics, statisticians involved in the industry as research scientists, regulators, academics, and/or consultants who want to know more about how to use S-PLUS and learn about other sub-fields within the industry, as well as statisticians in other fields who want to know more about statistical applications in the pharmaceutical industry.
Modern Applied Statistics with S-PLUS by William N. Venables,Brian D. Ripley Pdf
A guide to using the power of S-PLUS to perform statistical analyses, providing both an introduction to the program and a course in modern statistical methods. Readers are assumed to have a basic grounding in statistics, thus the book is intended for would-be users, as well as students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets, with many of the methods discussed being modern approaches to topics such as linear and non-linear regression models, robust and smooth regression methods, survival analysis, multivariate analysis, tree-based methods, time series, spatial statistics, and classification. This second edition is intended for users of S-PLUS 3.3, or later, and covers both Windows and UNIX. It treats the recent developments in graphics and new statistical functionality, including bootstraping, mixed effects linear and non-linear models, factor analysis, and regression with autocorrelated errors. The authors have written several software libraries which enhance S-PLUS, and these, plus all the datasets used, are available on the Internet.
National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics
Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics Publisher : National Academies Press Page : 219 pages File Size : 45,7 Mb Release : 2017-08-27 Category : Social Science ISBN : 9780309461672
Principles and Practices for a Federal Statistical Agency by National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics Pdf
Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens. In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit. Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence. Principles and Practices for a Federal Statistical Agency: Sixth Edition presents and comments on these principles as they've been impacted by changes in laws, regulations, and other aspects of the environment of federal statistical agencies over the past 4 years.
National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics
Author : National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics Publisher : National Academies Press Page : 136 pages File Size : 51,9 Mb Release : 2009-03-13 Category : Social Science ISBN : 9780309164320
Principles and Practices for a Federal Statistical Agency by National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics Pdf
Since 1992, the Committee on National Statistics (CNSTAT) has produced a book on principles and practices for a federal statistical agency, updating the document every 4 years to provide a current edition to newly appointed cabinet secretaries at the beginning of each presidential administration. This fourth edition presents and comments on four basic principles that statistical agencies must embody in order to carry out their mission fully: (1) They must produce objective data that are relevant to policy issues, (2) they must achieve and maintain credibility among data users, (3) they must achieve and maintain trust among data providers, and (4) they must achieve and maintain a strong position of independence from the appearance and reality of political control. The book also discusses 11 important practices that are means for statistical agencies to live up to the four principles. These practices include a commitment to quality and professional practice and an active program of methodological and substantive research. This fourth edition adds the principle that statistical agencies must operate from a strong position of independence and the practice that agencies must have ongoing internal and external evaluations of their programs.
Applied Data Science in Tourism by Roman Egger Pdf
Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau
Applied Data Analysis for Urban Planning and Management by Alasdair Rae,Cecilia Wong Pdf
This book showcases the different ways in which contemporary forms of data analysis are being used in urban planning and management. It highlights the emerging possibilities that city-regional governance, technology and data have for better planning and urban management - and discusses how you can apply them to your research. Including perspectives from across the globe, it’s packed with examples of good practice and helps to demystify the process of using big and open data. Learn about different kinds of emergent data sources and how they are processed, visualised and presented. Understand how spatial analysis and GIS are used in city planning. See examples of how contemporary data analytics methods are being applied in a variety of contexts, such as ‘smart’ city management and megacities. Aimed at upper undergraduate and postgraduate students studying spatial analysis and planning, this timely text is the perfect companion to enable you to apply data analytics approaches in your research.
