Probability r

Geometry, Analysis and Probability  eBooks & eLearning

Posted by arundhati at April 26, 2017
Geometry, Analysis and Probability

Jean-Benoît Bost, Helmut Hofer, "Geometry, Analysis and Probability: In Honor of Jean-Michel Bismut"
2017 | ISBN-10: 3319496360 | 361 pages | PDF | 4 MB

Matrix Algebra Useful for Statistics (Wiley Series in Probability and Statistics)  eBooks & eLearning

Posted by AlenMiler at April 13, 2017
Matrix Algebra Useful for Statistics (Wiley Series in Probability and Statistics)

Matrix Algebra Useful for Statistics (Wiley Series in Probability and Statistics) by Shayle R. Searle
English | 10 Apr. 2017 | ASIN: B06Y6DMXG5 | 512 Pages | AZW3 | 14.32 MB

Learning Bayesian Models with R  eBooks & eLearning

Posted by readerXXI at April 10, 2017
Learning Bayesian Models with R

Learning Bayesian Models with R
by Dr. Hari M. Koduvely
English | 2015 | ISBN: 178398760X | 165 Pages | True PDF | 1.48 MB

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems.

Schaum's Outline of Theory and Problems of Probability and Statistics (Repost)  eBooks & eLearning

Posted by leonardo78 at April 8, 2017
Schaum's Outline of Theory and Problems of Probability and Statistics (Repost)

Schaum's Outline of Theory and Problems of Probability and Statistics by Murray R. Spiegel
1975 | ISBN: 0070602204 | 372 pages | DJVU | 4,5 MB

This book gives theory and solved problems for a combined course in probability and mathematical statistics. A calculus background is employed.

A Natural Introduction to Probability Theory, 2nd edition (repost)  eBooks & eLearning

Posted by arundhati at April 7, 2017
A Natural Introduction to Probability Theory, 2nd edition (repost)

R. Meester, "A Natural Introduction to Probability Theory, 2nd edition"
2008 | ISBN-10: 3764387238 | 202 pages | PDF | 1 MB

Probability with Applications in Engineering, Science, and Technology, 2nd ed  eBooks & eLearning

Posted by nebulae at March 31, 2017
Probability with Applications in Engineering, Science, and Technology, 2nd ed

Carlton, Matthew A., Devore, Jay L., "Probability with Applications in Engineering, Science, and Technology, 2nd ed"
English | ISBN: 3319524011 | 2017 | 662 pages | PDF | 9 MB

Probability with Applications in Engineering, Science, and Technology, Second Edition  eBooks & eLearning

Posted by AvaxGenius at March 30, 2017
Probability with Applications in Engineering, Science, and Technology, Second Edition

Probability with Applications in Engineering, Science, and Technology, Second Edition By Matthew A. Carlton, Jay L. Devore
English | PDF | 2017 | 664 Pages | ISBN : 3319524003 | 13.13 MB

This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios.

Probability and Conditional Expectation: Fundamentals for the Empirical Sciences  eBooks & eLearning

Posted by nebulae at March 14, 2017
Probability and Conditional Expectation: Fundamentals for the Empirical Sciences

Rolf Steyer, Werner Nagel, "Probability and Conditional Expectation: Fundamentals for the Empirical Sciences"
English | ISBN: 1119243521 | 2017 | 600 pages | PDF | 4 MB

Probability & Statistics with R for Engineers and Scientists  eBooks & eLearning

Posted by interes at Feb. 22, 2017
Probability & Statistics with R for Engineers and Scientists

Probability & Statistics with R for Engineers and Scientists by Michael Akritas
English | 2015 | ISBN: 0321852990 | 528 pages | PDF | 7 MB

Fundamentals of R Programming and Statistical Analysis  eBooks & eLearning

Posted by FenixN at Feb. 7, 2017
Fundamentals of R Programming and Statistical Analysis

Fundamentals of R Programming and Statistical Analysis
HDRips | MP4/AVC, ~720 kb/s | 1280x720 | Duration: 06:46:40 | English: AAC, 128 kb/s (2 ch) | 1.8 GB
Genre: Development / Programming

A comprehensive guide to working on statistical data with the R language.