Thus, accurate and cost-effective models should be used for … Expand. View 2 excerpts, cites methods. View 1 excerpt, cites methods.
Particle sensing technology has shown great potential for monitoring particulate matter PM with very few temporal and spatial restrictions because of low-cost, compact size, and easy … Expand. Underwriters, as well as issuers, show ambiguity toward the flipping activity or selling initially public offered stocks IPO stocks in the first trading day.
On one side, they are naturally against … Expand. View 3 excerpts, cites background. High school learners' perceptions of accounting as a career path in the Mafikeng area. Guidelines for the modelling of statistical data and metadata.
Highly Influential. View 3 excerpts, references background and methods. A nationally representative case-control study of smoking and death in India. View 1 excerpt. Bad Pharma: How drug companies mislead doctors and harm patients. How to lie With Statistics. View 1 excerpt, references background.
The Concise Encyclopedia of Statistics. The Concise Encyclopedia of Statistics presents the essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the … Expand. Efficacy of a theory-based behavioural intervention to increase physical activity in an at-risk group in primary care ProActive UK : a randomised trial. Goodchild, and Paul A. The Tiger That Isn't. More precisely, it is organic, with new functionality and add-on packages appearing constantly.
And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields. Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application.
This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce.
Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications.
This handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport baseball, football, hockey, basketball, and soccer followed by a section on other sports and general statistical design and analysis issues that are common to all sports.
This handbook has the potential to become the standard reference for obtaining the necessary background to conduct serious statistical analyses for sports applications and to appreciate scholarly work in this expanding area. With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. This edition covers many new features of Stata, including a new command for mixed models and a new matrix language.
Each chapter describes the analysis appropriate for a particular application, focusing on the medical, social, and behavioral fields. The authors begin each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests, variance analysis, multiple linear regression, logistic regression, generalized linear models, survival analysis, random effects models, and cluster analysis.
The core of the book centers on how to use Stata to perform analyses and how to interpret the results. The chapters conclude with several exercises based on data sets from different disciplines. A concise guide to the latest version of Stata, A Handbook of Statistical Analyses Using Stata, Fourth Edition illustrates the benefits of using Stata to perform various statistical analyses for both data analysis courses and self-study.
New to the Third Edition. This comprehensive professional reference for scientists, engineers, and researchers brings together in a single resource all the information a beginner will need to rapidly learn how to conduct data mining and the statistical analysis required to interpret the data once mined. A glossary of data mining terms provided in the appendix.
As the software supporting statistical analysis has grown in breadth and depth to the point where it can serve many of the needs of accomplished statisticians it can also serve as an essential support to those needing to expand their knowledge of statistical applications.
Statisticians should not be handicapped by heavy computation or by the lack of needed options. When Applied Statistics, Principle and Examples by Cox and Snell appeared we at BMDP were impressed with the scope of the applications discussed and felt that many statisticians eager to expand their capabilities in handling such problems could profit from having the solutions carried further, to get them started and guided to a more advanced level in problem solving.
Who would be better to undertake that task than the authors of Applied Statistics? A year or two later discussions with David Cox and Joyce Snell at Imperial College indicated that a wedding of the problem statements and suggested solutions with control language to accomplish these analyses would further the learning process for many statisticians.
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