Introduction to Nonparametric Regression

Introduction to Nonparametric Regression (Repost)  eBooks & eLearning

Posted by Specialselection at Jan. 22, 2014
Introduction to Nonparametric Regression (Repost)

K. Takezawa, "Introduction to Nonparametric Regression"
English | 2005-11-25 | ISBN: 0471745839 | 557 pages | DJVU | 3.6 mb

Introduction to Linear Regression Analysis (5th Edition)  eBooks & eLearning

Posted by Jeembo at Dec. 21, 2016
Introduction to Linear Regression Analysis (5th Edition)

Introduction to Linear Regression Analysis (5th Edition) by Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
English | 2012 | ISBN: 0470542810 | 672 Pages | PDF | 33.1 MB

Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research.
Solutions Manual to Accompany Introduction to Linear Regression Analysis, 5 edition (repost)

Solutions Manual to Accompany Introduction to Linear Regression Analysis, 5 edition by Ann G. Ryan, Douglas C. Montgomery, Elizabeth A. Peck and G. Geoffrey Vining
English | 2013 | ISBN: 1118471466 | ISBN-13: 9781118471463 | 164 pages | PDF | 45,3 MB

Introduction to Nonparametric Statistics for the Biological Sciences Using R  eBooks & eLearning

Posted by AlenMiler at July 12, 2016
Introduction to Nonparametric Statistics for the Biological Sciences Using R

Introduction to Nonparametric Statistics for the Biological Sciences Using R by Thomas W. MacFarland
English | 13 Aug. 2016 | ISBN: 3319306332 | 348 Pages | PDF (True) | 5.13 MB

This book contains a rich set of tools for nonparametric analyses, and the purpose of this supplemental text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences…
Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling, 2nd Edition

Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling, 2nd Edition by Timothy Keith
2014 | ISBN: 1138811947, 1138811955 | English | 600 pages | PDF | 5 MB
Solutions Manual to Accompany Introduction to Linear Regression Analysis, 5 edition

Solutions Manual to Accompany Introduction to Linear Regression Analysis, 5 edition by Ann G. Ryan, Douglas C. Montgomery, Elizabeth A. Peck and G. Geoffrey Vining
English | 2013 | ISBN: 1118471466 | ISBN-13: 9781118471463 | 164 pages | PDF | 45,3 MB

As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research.
Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition

Julian J. Faraway, "Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition"
English | ISBN: 149872096X | 2017 | 413 pages | PDF | 43 MB

A Gentle Introduction to Stata, Fourth Edition (repost)  eBooks & eLearning

Posted by interes at Feb. 19, 2017
A Gentle Introduction to Stata, Fourth Edition (repost)

A Gentle Introduction to Stata, Fourth Edition by Alan C. Acock
English | 2014 | ISBN: 1597181420 | 500 pages | PDF | 6,4 MB
Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance (repost)

Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance by Jussi Klemelä
English | 2014 | ISBN: 0470384425 | ISBN-13: 9780470384428 | 396 pages | PDF | 19,8 MB

Introduction to QGIS Python Programming  eBooks & eLearning

Posted by FenixN at Dec. 3, 2016
Introduction to QGIS Python Programming

Introduction to QGIS Python Programming
HDRips | MP4/AVC, ~611 kb/s | 1280x720 | Duration: 03:32:55 | English: AAC, 128 kb/s (2 ch) | 777 MB
Genre: Development / Programming

Learn how to analyze and display geospatial information using QGIS and Python.