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Code of Safe Working Practices for Merchant Seafarers
Author: The Stationery Office
language: en
Publisher: Stationery Office Books (TSO)
Release Date: 2018-01-18
Amendment to 2015 consolidated ed. (ISBN 9780115534027). Amendment consists of loose-leaf pages that replace select pages from the main edition binder
The Theory and Practice of Online Learning
Author: Terry Anderson
language: en
Publisher: Athabasca University Press
Release Date: 2008
"Neither an academic tome nor a prescriptive 'how to' guide, The Theory and Practice of Online Learning is an illuminating collection of essays by practitioners and scholars active in the complex field of distance education. Distance education has evolved significantly in its 150 years of existence. For most of this time, it was an individual pursuit defined by infrequent postal communication. But recently, three more developmental generations have emerged, supported by television and radio, teleconferencing, and computer conferencing. The early 21st century has produced a fifth generation, based on autonomous agents and intelligent, database-assisted learning, that has been referred to as Web 2.0. The second edition of "The Theory and Practice of Online Learning" features updates in each chapter, plus four new chapters on current distance education issues such as connectivism and social software innovations."--BOOK JACKET.
All of Statistics
Author: Larry Wasserman
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-12-11
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.