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24/7 Training for Data Analysis and Statistics Software: E-Resources from the Library

Decorative: book to e-book learning conceptIf you write scripts or use data analysis software, did you know that the Health Sciences Library System provides access to thousands of reference materials to help support research programming in the health sciences? If you want to test out software or need help interpreting a never-before-seen error message, the library’s streaming videos and e-books are available to anyone with a Pitt ID, on- or off-campus.

LinkedIn Learning (formerly known as Lynda.com) provides video tutorials, transcripts, and exercises for popular data analysis and statistics software. Need an introduction to SPSS? Try the SPSS Statistics Essential Training course to learn the basics, or focus on quantitative tests in SPSS for Academic Research course. Dive deep into SAS with a multi-part series of SAS Essential Training: Descriptive Analysis for Healthcare Research and SAS Essential Training: Regression Analysis for Healthcare Research. Introductions to Stata and MATLAB are also available.

Beyond software, LinkedIn Learning offers courses in programming languages such as Learning R or Learning Python, and encourages you to put those skills to work in applied courses like Python Statistics Essential Training. Learn to version-control all your code with Learning Github. Or start with the basics in Programming Foundations: Fundamentals or Statistics Foundations 1, 2, and 3.

If you only want to get a feel for the software, don’t be put off by the time commitment. Each course is subdivided into lessons so you can watch only what you need, and you can save videos to a playlist to watch later. I’ve compiled all of these courses and more into a public playlist that Pitt users can access here: Software Resources for Health Sciences.

Reference books remain a quick way to find specific information, and many software manuals are available as library e-books. (Off-campus, just sign in via remote access before reading.) Take a look at the Python references and R textbooks available instantly through the catalog, or the guides for SPSS, Stata, SAS, MATLAB, Excel, or Github. For statistics in the health sciences, try HSLS’ curated list of e-books covering statistics. If you’re in molecular biology, the Molecular Biology Information Service provides guides for the software they support via MolBio Licensed Tools.

Have a suggestion for software we should consider, or want to meet with a librarian about writing readmes or documenting and sharing software? Check out our list of classes and contact the Data Services team at HSLSDATA@pitt.edu.

~Helenmary Sheridan

Posted in the July 2019 Issue     

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