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eReads & Reference. An exclusive PMI member benefit, eReads & Reference provides online access to 250 complete and unabridged books from PMI and other leading publishers.

eReads & Reference

Topics include project management, leadership, teams, cross-cultural business, knowledge management and more. With eReads & Reference it's easy to expand your project management horizons online, anytime. Powered by Books 24x7's sophisticated search engine, eReads & Reference lets you find books by keyword, phrase, title, author, publisher or International Standard Book Number (ISBN). Use eReads Reference as an on-the-job guide, a research and study aid, or to preview books before you buy. For quick reference, bookmark titles of interest or build your own bookshelf.

Not a PMI member? Member Picks The following are among the top titles accessed by current eReads & Reference users. Q&As for the PMBOK ® Guide — Fourth Edition Edited by Dr. Types of PMI Memberships. Individual Member Our individual membership is open to anyone interested in project management.

Types of PMI Memberships

If your work involves projects or project management, or you simply want to learn more about them, an individual membership is a terrific solution for you. Pricing: Join or renew now or download an application. Student Member PMI memberships aren't just for working project practitioners. Your membership publications will be delivered electronically to your email address. Join or renew now or download an application Retiree Member Your enthusiasm for project management doesn't have to end when you stop working. Free project management templates and project management information. Project management training and consulting in Seattle Bellevue and Tucson. Sharing by design. Labs. CA Technologies is committed to advancing technology research in areas of strategic importance to our company.


Through CA Labs, we partner with both internal and external organizations to further innovation in enterprise IT management. We engage with academia, professional associations, industry standards bodies, customers and partners to explore novel products and emerging technologies. CA Labs was established in 2005 to strengthen relationships between research communities and CA Technologies.

CA Labs works closely with universities, professional associations and government organizations on various projects that relate to our company’s products, technologies and methodologies. The results of these projects vary from research publications, to best practices, to new directions for products. Research Areas CA Labs conducts advanced research related to enterprise information technology management.

People CA Labs scientists and engineers are among the most distinguished in their fields. Graduate Schools - Postgraduate Courses Worldwide. MyPhDNetwork. The PhD Project: Academic Job Sites. The PhD Project: Real World Success. The PhD Project: Considering The PhD Project. North American Rankings - UTD Top 100 Business School Research Rankings™ - School of Management @ UT Dallas. Research Policy Handbook. NOTE: As of March 1, 2013, this web site has been incorporated into the Stanford University DoResearch web site .

Research Policy Handbook

Many links will be automatically redirected. If you have bookmarks or other links to this page, please change them to This Handbook addresses the conduct of research, i.e., systematic investigation designed to develop or contribute to generalizable knowledge , at Stanford. A complete Table of Contents of the Research Policy Handbook, including policy dates, is available (pdf file). A NOTE ABOUT PRINTING: There is a "Print this page" link in the upper right corner of each document in this collection, providing a "printer-friendly" file. Contact Ann George if you have questions about this handbook. What's New in the Research Policy Handbook As documents are updated, or new documents are added, you will see a notice to that effect here.

Stanford University reserves the right to amend at any time the policies and other materials contained in this handbook. Philanthropy and Civil Society. Independent Laboratories, Institutes and Centers. Business Magazine Winter 2011. Some 140 years ago, Leland Stanford became intrigued by what seemed like a straightforward question but was a matter of real debate among horseracing enthusiasts: Does a running horse at some point in its gait maintain all four feet off the ground? To find out, Stanford invited the photographer Eadweard Muybridge to conduct a series of experiments. On what’s now part of Stanford University campus, he set up a series of cameras triggered by trip wires to snap a quick series of shots as Stanford’s Kentucky-bred mare Sallie Gardner galloped around a track.

Their finding, to the surprise of both the art and science communities, was that the answer was yes. Stanford’s efforts to discover the answer to this question is illustrative of something deep in the DNA of the university he founded soon after: a thirst for knowledge and understanding, and for innovative approaches to problem solving. Stanford Business celebrates these values. In this issue, you will find stories that echo these ideals. Decision tree learning. Decision tree learning uses a decision tree as a predictive model which maps observations about an item to conclusions about the item's target value.

Decision tree learning

It is one of the predictive modelling approaches used in statistics, data mining and machine learning. More descriptive names for such tree models are classification trees or regression trees. In these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels. In decision analysis, a decision tree can be used to visually and explicitly represent decisions and decision making. In data mining, a decision tree describes data but not decisions; rather the resulting classification tree can be an input for decision making. General[edit] A tree showing survival of passengers on the Titanic ("sibsp" is the number of spouses or siblings aboard). A decision tree is a simple representation for classifying examples. Data comes in records of the form: Types[edit] Metrics[edit]