| 词条 | Statistics Online Computational Resource |
| 释义 |
| name = Statistics Online Computational Resource (SOCR) | image = SOCR OverviewImage 2009.jpg | size = 150px | motto = It's Online, therefore it exists! | focus = scientific computing, data analytics, visualization, inference, education | founded = January 5, 2002 | type = not-for-profit | website = www.socr.umich.edu | coords = {{Coord|42.284199|-83.738072}} }} The Statistics Online Computational Resource (SOCR)[1] is an online multi-institutional research and education organization. SOCR designs, validates and broadly shares a suite of online tools for statistical computing, and interactive materials for hands-on learning and teaching concepts in data science, statistical analysis and probability theory. The SOCR resources are platform agnostic based on HTML, XML and Java, and all materials, tools and services are freely available over the Internet. The core SOCR components include interactive distribution calculators, statistical analysis modules, tools for data modeling, graphics visualizaiton, instructional resources, learning activities and other resources[2] .[3] All SOCR resources are LGPL/CC-BY licensed, peer-reviewed, integrated internally and interoperate with independent digital libraries developed by other professional societies and scientific organizations[4] like NSDL, Open Educational Resources, Mathematical Association of America, California Digital Library, LONI Pipeline, etc. See also
External links
References1. ^{{cite journal| first= Ivo D. |last=Dinov |author2=Sanchez, Juana |author3=Christou, Nicolas | title=Pedagogical Utilization and Assessment of the Statistic Online Computational Resource in Introductory Probability and Statistics Courses | journal=Computers and Education | year=2008| volume= 50| issue=1 |pages=284–300 | doi=10.1016/j.compedu.2006.06.003| pmid= 19750185| pmc= 2740633}} 2. ^{{cite journal| first= Ivo D. |last=Dinov| title=Statistics Online Computational Resource | journal=Journal of Statistical Software | year=2006| volume= 16| pages=1–16 | url=http://www.jstatsoft.org/v16/i11| issue=1}} 3. ^{{cite journal| first= Nicolas |last=Christou|author2=Dinov, I. | title=A Study of Students’ Learning Styles, Discipline Attitudes and Knowledge Acquisition in Technology-Enhanced Probability and Statistics Education| journal=Journal of Online Learning and Teaching | year=2010| volume= 6 | pages=546–572 | url=http://jolt.merlot.org/vol6no3/dinov_0910.pdf| issue=3}} 4. ^Peer-reviewed SOCR papers and SOCR integration in international digital libraries 5 : Educational math software|Educational websites|Research institutes in the United States|Statistical software|University of Michigan |
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