Association Analysis r

Behavioral Approaches to Medicine: Application and Analysis  eBooks & eLearning

Posted by step778 at Dec. 7, 2016
Behavioral Approaches to Medicine: Application and Analysis

John R. McNamara, "Behavioral Approaches to Medicine: Application and Analysis"
1979 | pages: 327 | ISBN: 1461591244 | PDF | 47,5 mb
The Evolution of Applied Harmonic Analysis: Models of the Real World (Applied and Numerical Harmonic Analysis)

The Evolution of Applied Harmonic Analysis: Models of the Real World (Applied and Numerical Harmonic Analysis) by Elena Prestini
English | 20 Dec. 2016 | ISBN: 1489979875 | 382 Pages | PDF | 15.99 MB
Probability Methods for Cost Uncertainty Analysis: A Systems Engineering Perspective, 2nd Edition

Paul R. Garvey, Stephen A. Book, Raymond P. Covert "Probability Methods for Cost Uncertainty Analysis: A Systems Engineering Perspective, 2nd Edition"
English | 2015 | ISBN: 1482219751 | 524 pages | PDF | 9.6 MB
Statistics and Data Analysis for Microarrays Using R and Bioconductor (2nd Edition) (Repost)

Statistics and Data Analysis for Microarrays Using R and Bioconductor (2nd Edition) By Sorin Draghici
2012 | 1036 Pages | ISBN: 1439809755 | PDF | 131 MB
Behavior, Truth and Deception: Applying Profiling and Analysis to the Interview Process (Repost)

Behavior, Truth and Deception: Applying Profiling and Analysis to the Interview Process By Michael R. Napier
2010 | 394 Pages | ISBN: 1439820414 | PDF | 18 MB
Andrea S. Foulkes - Applied Statistical Genetics with R: For Population-based Association Studies [Repost]

Andrea S. Foulkes - Applied Statistical Genetics with R: For Population-based Association Studies
2009 | ISBN: 0387895531 | English | 264 pages | PDF | 2.5 MB

A Companion to Analysis: A Second First and First Second Course in Analysis  eBooks & eLearning

Posted by MoneyRich at Nov. 21, 2016
A Companion to Analysis: A Second First and First Second Course in Analysis

A Companion to Analysis: A Second First and First Second Course in Analysis by T. W. K├Ârner
English | 30 Nov. 2003 | ISBN: 0821834479 | 590 Pages | PDF | 26 MB

Many students acquire knowledge of a large number of theorems and methods of calculus without being able to say how they work together. This book provides those students with the coherent account that they need. ""A Companion to Analysis"" explains the problems that must be resolved in order to procure a rigorous development of the calculus and shows the student how to deal with those problems.

An Introduction to Data Analysis using Aggregation Functions in R  eBooks & eLearning

Posted by Underaglassmoon at Nov. 18, 2016
An Introduction to Data Analysis using Aggregation Functions in R

An Introduction to Data Analysis using Aggregation Functions in R
Springer | Artificial Intelligence | December 5, 2016 | ISBN-10: 3319467611 | 199 pages | pdf | 4.56 mb

Authors: James, Simon
Provides an overview of aggregation functions
Includes hands-on tutorials on how to program the functions covered in R without needing extensive programming courses
Does not assume a mathematics background
Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection

Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection by Yun Sing Koh
English | 30 Aug. 2009 | ISBN: 1605667544 | 301 Pages | PDF | 9 MB

The growing complexity and volume of modern databases make it increasingly important for researchers and practitioners involved with association rule mining to make sense of the information they contain.

Learning Path: R Programming for Data Analysts  eBooks & eLearning

Posted by FenixN at Nov. 16, 2016
Learning Path: R Programming for Data Analysts

Learning Path: R Programming for Data Analysts
HDRips | MP4/AVC, ~1500 kb/s | 960x528 | Duration: 15:12:01 | English: AAC, 128 kb/s (2 ch) | 5,46 GB
Genre: Development / Programming

R Programming Data Analyst Learning Path, is a tour through the most important parts of R, the statistical programming language, from the very basics to complex modeling. It covers reading data, programming basics, visualization, data munging, regression, classification, clustering, modern machine learning, network analysis, web graphics, and techniques for dealing with large data, both in memory and in databases.