Guide To Information Sources In Mathematics And Statistics
Download Guide To Information Sources In Mathematics And Statistics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Guide To Information Sources In Mathematics And Statistics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Guide to Information Sources in Mathematics and Statistics
Author: Martha A. Tucker
language: en
Publisher: Bloomsbury Publishing USA
Release Date: 2004-09-30
This book is a reference for librarians, mathematicians, and statisticians involved in college and research level mathematics and statistics in the 21st century. We are in a time of transition in scholarly communications in mathematics, practices which have changed little for a hundred years are giving way to new modes of accessing information. Where journals, books, indexes and catalogs were once the physical representation of a good mathematics library, shelves have given way to computers, and users are often accessing information from remote places. Part I is a historical survey of the past 15 years tracking this huge transition in scholarly communications in mathematics. Part II of the book is the bibliography of resources recommended to support the disciplines of mathematics and statistics. These are grouped by type of material. Publication dates range from the 1800's onwards. Hundreds of electronic resources-some online, both dynamic and static, some in fixed media, are listed among the paper resources. Amazingly a majority of listed electronic resources are free.
Reference Sources for Small and Medium-sized Libraries, Eighth Edition
Author: Jack O'Gorman
language: en
Publisher: American Library Association
Release Date: 2014-02-25
Focusing on new reference sources published since 2008 and reference titles that have retained their relevance, this new edition brings O’Gorman’s complete and authoritative guide to the best reference sources for small and medium-sized academic and public libraries fully up to date. About 40 percent of the content is new to this edition. Containing sources selected and annotated by a team of public and academic librarians, the works included have been chosen for value and expertise in specific subject areas. Equally useful for both library patrons and staff, this resource Covers more than a dozen key subject areas, including General Reference; Philosophy, Religion, and Ethics; Psychology and Psychiatry; Social Sciences and Sociology; Business and Careers; Political Science and Law; Education; Words and Languages; Science and Technology; History; and Performing Arts Encompasses database products, CD-ROMs, websites, and other electronic resources in addition to print materials Includes thorough annotations for each source, with information on author/editor, publisher, cost, format, Dewey and LC classification numbers, and more Library patrons will find this an invaluable resource for current everyday topics. Librarians will appreciate it as both a reference and collection development tool, knowing it’s backed by ALA’s long tradition of excellence in reference selection.
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.