Vincent Granville lists several good articles on clustering. This resource is part of a series on specific topics related to data science. To receive notices about these kinds of articles, sign up on DSC.
Vincent Granville lists several good articles and tutorials about correlation. This resource is part of a series on specific topics related to data science. To receive notices about these resources, sign up on DSC.
Suni Kappal posts his list of the most common basic analytical and statistical mistakes. He divides his list into visualization errors and statistical blunders. See his blog entry at http://www.datasciencecentral.com/profiles/blogs/the-most-common-analytical-and-statistical-mistakes
ALA is offering two 90-minute webinar sessions by Emily Daly and Joyce Chapman on using surveys to improve libraries. The workshops will be held February 1 and 8 at 2:30pm Eastern. The cost is $75. For details, go to http://www.alastore.ala.org/detail.aspx?ID=11894&zbrandid=4634&zidType=CH&zid=39911004&zsubscriberId=1026813538&zbdom=http://ala-publishing.informz.net
The Canadian journal Evidence Based Library and Information Practice shares research that informs professional library practice. The winter 2016 issue (https://ejournals.library.ualberta.ca/index.php/EBLIP) exemplifies this mission, having several data-based articles:
Amy Jo Catalano , Sharon Rose Phillips
Identifying and Classifying User Typologies Within a United Kingdom Hospital Library Setting: A Case Study
Alison Ambi , Pamela Morgan , Erin Alcock , Amanda Tiller-Hackett
Lynn Easton , Scott Adam , Trish Durnan , Lorraine McLeod
Manish Saraswat introduces crucial concepts of regression analysis with practice in R. The article focuses on linear and multiple regression: http://www.datasciencecentral.com/profiles/blogs/beginners-guide-to-regression-analysis-and-plot-interpretations
Laetitia Van Cauwenberge’s blog describes 11 important model evaluation techniques to assess goodness of fit between model and data. Read more at http://www.datasciencecentral.com/profiles/blogs/7-important-model-evaluation-error-metrics-everyone-should-know
This two-part blog provides background information, and 24 popular uses of statistical, data science, machine learning, optimization, graph theory, mathematical and operations research techniques. Read more at http://www.datasciencecentral.com/profiles/blogs/24-uses-of-statistical-modeling-part-ii
Open data is data that “can be freely used, modified and shared by anyone for any purpose” (http://opendefinition.org/). Open data increases access, preservation, and impact. Increasingly, it is also a requirement as part of federal funding.
Librarians can facilitate its collection, organization, and its physical and intellectual access. Librarians can also help researchers in grantsmanship.
American Library Association’s EBSS section suggests these resources:
Here is another list of free data sets: http://www.datasciencecentral.com/forum/topics/more-free-data-sets