Posted by **interes** at May 1, 2015

English | 2014 | ISBN: 1439887330 | 286 pages | PDF | 1,7 MB

Posted by **interes** at Oct. 28, 2014

English | 2004 | ISBN: 1584884258 | 240 pages | PDF | 10,6 MB

This textbook focuses on the practice of regression and analysis of variance. Readers will learn which methods are available and the various situations in which they can be applied. Numerous examples clarify the use of the techniques and demonstrate what conclusions can be made.

Posted by **ChrisRedfield** at Aug. 4, 2014

Published: 2005-12-20 | ISBN: 158488424X | PDF | 312 pages | 3 MB

Posted by **enmoys** at May 26, 2016

2015 | 168 Pages | ISBN: 178398760X | EPUB | 3 MB

Posted by **tanas.olesya** at April 5, 2016

English | 28 Oct. 2015 | ISBN: 178398760X | 191 Pages | EPUB | 3 MB

This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications.

Posted by **naag** at Jan. 21, 2016

MP4 | Video: AVC (.mp4) 1280x720 | Audio: AAC 48KHz 2ch | Duration: 6.5 Hours | 1.30 GB

Learn main forecasting models from basic to expert level through a practical course with R statistical software.

Posted by **naag** at Dec. 21, 2015

MP4 | Video: 1280x720 | 60 kbps | 44 KHz | Duration: 15 Hours | 3.49 GB

Learn to model with R: ANOVA, regression, GLMs, survival analysis, GAMs, mixed-effects, split-plot and nested designs

Posted by **libr** at Dec. 11, 2015

English | May 24, 2011 | ISBN: 0470745843 | 478 pages | PDF | 4,4 MB

Posted by **fdts** at Nov. 23, 2015

by Faraway J.

English | 2005 | ISBN: 0203492285 | 312 pages | PDF | 7.78 MB

Posted by **AlenMiler** at Oct. 30, 2015

English | 28 Oct. 2015 | ISBN: 178398760X | 168 Pages | AZW3 (Kindle)/HTML/EPUB/PDF (conv) | 19 MB

This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications.