Posted by **arundhati** at March 5, 2017

2015 | 356 Pages | ISBN: 1484203747 | PDF | 11 MB

Posted by **insetes** at Nov. 30, 2015

2015 | 356 Pages | ISBN: 1484203747 | PDF | 11 MB

Posted by **Willson** at Oct. 5, 2015

English | 2012 | ISBN: 1430245549 | 336 pages | PDF | 8.3 MB

Posted by **ChrisRedfield** at June 23, 2014

Published: 2012-10-17 | ISBN: 1430245549 | PDF | 336 pages | 4 MB

Posted by **zolao** at Aug. 16, 2013

2012 | ISBN-10: 1430245549 | PDF | 336 pages | 11 MB

Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T.

Posted by **zolao** at July 19, 2013

2012 | ISBN-10: 1430245549 | PDF, EPUB | 336 pages | 11 + 6 MB

Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T.

Posted by **zolao** at July 11, 2013

2012 | ISBN-10: 1430245549 | PDF, EPUB | 336 pages | 11 + 6 MB

Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T.

Posted by **arundhati** at March 29, 2017

2015 | ISBN-10: 1305269470 | 1296 pages | PDF | 43 MB

Posted by **tarantoga** at Feb. 15, 2017

ISBN: 1461471370 | 2013 | EPUB | 426 pages | 4 MB

Posted by **hill0** at Feb. 3, 2017

English | 4 Apr. 2012 | ISBN: 041588005X | 840 Pages | PDF | 34.39 MB

This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results. Key concepts are simply stated and occasionally reintroduced and related to one another for reinforcement. Numerous examples demonstrate their relevance.