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Exploratory Data Analysis: An Introduction to Data Analysis Using SAS
This is an introductory text on how to investigate datasets. It is intended to be a practical text for those who need to research large datasets. Therefore, it does not follow the standard contents for more typical introductory statistics textbooks. When you complete the material, you will be able to work with your data using data visualization and regression in order to make sense of it, and to use your findings to make decisions. The book makes use of the statistical software, SAS, and its menu system SAS Enterprise Guide. This can be used as a stand alone text, or as a supplementary text to a more standard course. There are some datasets to accompany this text. ID# 1640751, Data for Exploratory Data Analysis.
Cases on Health Outcomes and Clinical Data Mining: Studies and Frameworks
"Because so much data is now becoming readily available to investigate health outcomes, it is important to examine just how statistical models are used to do this. This book studies health outcomes research using data mining techniques"--Provided by publisher.
Clinical Data Mining for Physician Decision Making and Investigating Health Outcomes: Methods for Prediction and Analysis
"This book shows how the investigation of healthcare databases can be used to examine physician decisions to develop evidence-based treatment guidelines that optimize patient outcomes"--Provided by publisher.
Progress in Oncology 2002
The second volume in the annual series, Progress In Oncology 2002 highlights progress in the basic and clinical aspects of oncology and is reviewed by leaders in the field. Comprehensive reviews on important advances in the previous year are selected to help cancer research scientists and oncologists stay up-to-date with high impact progress across all disciplines in oncology.
Pharmaceutical Statistics Using SAS
Introduces a range of data analysis problems encountered in drug development and illustrates them using case studies from actual pre-clinical experiments and clinical studies. Includes a discussion of methodological issues, practical advice from subject matter experts, and review of relevant regulatory guidelines.
Validating Clinical Trial Data Reporting with SAS
This indispensable guide focuses on validating programs written to support the clinical trial process from after the data collection stage to generating reports and submitting data and output to the Food and Drug Administration.
Advanced Computational Intelligence Paradigms in Healthcare - 1
This volume presents some of the most recent research results on the applications of computational intelligence in healthcare. It is directed at computer scientists, medical practitioners, scientists, professors and students of health, science, computer science and related disciplines.
Data Preparation for Analytics Using SAS
Text addresses such tasks as: viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis, and using SAS procedures for scoring.
Tennessee Topology Conference
Contents:Endomorphism Properties of Algebraic Structures (M E Adams et al.)Alternate Methods for Generating Interaction Semigroups (G R Barnes et al.)Separate vs. Joint Continuity: A Tale of Four Topologies — A Summary (M Henriksen)Cardinal Functions on Continuous Images (I Juhász)A Survey of Topological Nearrings and Nearrings of Continuous Functions (K D Magill, Jr.)Ordered Quotients and the Semi-Lattice of Ordered Compactifications (D D Mooney & T A Richmond)Various Topologies on Trees (P J Nyikos)Backward Shifts on Banach Spaces C(X), II (M Rajagopalan & K Sundaresan)and other papers Readership: Mathematicians.
Proceedings of the Third SIAM International Conference on Data Mining
The third SIAM International Conference on Data Mining provided an open forum for the presentation, discussion and development of innovative algorithms, software and theories for data mining applications and data intensive computation. This volume includes 21 research papers.
