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  1. Added Jun 09, 2009 by gutman_librarians
    Education Week's 4th annual Diplomas Count report: Broader Horizons: The Challenge of College Readiness for All Students.
  2. Added Jan 06, 2009 by gutman_librarians
    CDF's State of America's Children 2008 report is a compilation of recent national and state-by-state data on poverty, health, child welfare, youth at risk, early childhood development, education, nutrition and housing.
  3. Added Dec 20, 2008 by sanchye
    This article shares some statistics on cyberbullying.
  4. Added Dec 18, 2008 by jillianeorr
    From the site: "Via web application software, data citation standards, and statistical methods, the Dataverse Network project increases scholarly recognition and distributed control for authors, journals, archives, teachers, and others who produce or organize data; facilitates data access and analysis for researchers and students; and ensures long-term preservation..."
  5. Added Dec 10, 2008 by gutman_librarians
    This report presents 2006-07 school year information at the national and state level on student enrollment by grade and by race/ethnicity within grade, the numbers of teachers and other education staff, and several student/staff ratios.
  6. Added Oct 01, 2008 by julieerose
    Interesting statistics about how cell phones are used more to text than to make phone calls. And teenagers can text blindfolded!
  7. Added Jun 04, 2008 by gutman_librarians
    Education Week special issue on states' efforts to forge stronger connections between precollegiate and postsecondary education
  8. Added Apr 22, 2008 by gutman_librarians
    The American Association of University Professors' annual look at faculty salaries in colleges and universities.
  9. Added Nov 25, 2007 by aseldow and 1 other
    The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms. These include classification algorithms such as decision trees, neural nets, Bayesian classifiers, Support Vector Machines and cased-based...
  10. Added Nov 12, 2007 by kellyleahy and 1 other
    my goal with this blog is to explore some of the assumptions underlying "popular" visualization design and reception, in the hopes of uncovering some practical, unifying principles that could be applied to future design. Or, at the very least, draw attention to some of the existing design issues in the hopes that awareness and discussion of them will result in more informed design.
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