Posted by **naag** at Feb. 13, 2016

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 223 MB

Learn through clear lectures and hands-on solved problems how to fully understand the Normal Distribution.

Posted by **hill0** at Sept. 27, 2017

English | 2017 | ISBN: 331952206X | 534 Pages | PDF | 4.79 MB

Posted by **ChrisRedfield** at Nov. 13, 2017

Published: 2015-05-30 | ISBN: 3319171321 | PDF | 91 pages | 2.56 MB

Posted by **arundhati** at Oct. 30, 2017

2017 | ISBN-10: 3319513125 | 220 pages | EPUB | 4 MB

Posted by **hill0** at Oct. 26, 2017

English | 3 July 2017 | ISBN: 9811048541 | 642 Pages | EPUB | 11.02 MB

This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research,

Posted by **First1** at Oct. 26, 2017

English | 2017 | ISBN: 3319456148 | 236 Pages | EPUB | 2.30 MB

Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing.

Posted by **libr** at Oct. 24, 2017

English | 2014 | ISBN: 1493906909 | 107 pages | PDF | 3,6 MB

Posted by **arundhati** at Oct. 23, 2017

2016 | ISBN-10: 1446210448, 1446210456 | 768 pages | PDF | 35 MB

Posted by **leonardo78** at Oct. 20, 2017

Language: English | 2010 | ISBN: 1592293298 | 517 pages | PDF | 71,8 MB

Whether you're a consultant or project lead, this is the book you need to learn how to configure and use SAP SD to optimize your sales and distribution processes and streamline your business.

Posted by **AvaxGenius** at Oct. 12, 2017

English | PDF,EPUB | 2017 | 664 Pages | ISBN : 3319648667 | 12.91 MB

This textbook for graduate and advanced undergraduate students presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra. Matrix algebra is one of the most important areas of mathematics in data science and in statistical theory, and the second edition of this very popular textbook provides essential updates and comprehensive coverage on critical topics in mathematics in data science and in statistical theory.