All of the following tools are freely available, have a free option (freemium), or available through Northwell or the ZSOM (access directions indicated).
Tableau (Available to users with Hofstra email addresses via PrideDesktop. Click here for access instructions. Or, visit the Northwell Tableau Page)
A tool to produce advanced graphics with numeric and categorical data. Also includes some analysis tools. Learn about Tableau here.
Tableau also has a free version, Tableau Public.
BioRender (Access through Zucker SOM Library)
Online tool for creating scientific figures. Tutorials here.
VOSviewer (free)
A tool for creating, visualizing, and exploring bibliometric maps of science. Tutorial here
RAWGraphs (free)
A web-browser based data visualization tool that is easy to navigate for users unfamiliar with statistics and data sets. Tutorials here
Datawrapper (free)
An open source data visualization platform helping everyone to create simple, correct and embeddable charts in minutes. Tutorials here
An extensive list of data visualization tools compiled by University of Buffalo is available here.
Nomic Atlas (freemium)
Create a cloud visualization from unstructured data.
ArcGIS (Available to users with Hofstra email addresses via Pride Desktop. Click here for access instructions.)
Powerful software for geospatial data analysis. Learn ArcGIS
ArcGIS online (freemium)
Platform created by ESRI (makers of ArcGIS) focused on online storytelling with maps.
QGIS (free)
Open source alternative to ArcGIS. QGIS Tutorials
Scribble Maps (freemium)
Custom map builder, based on google maps. Training playlist on YouTube
SPSS (Available to users with Hofstra email addresses via Pride Desktop. Click here for access instructions.)
A software designed to solve business and research problems through ad hoc analysis, hypothesis testing, geospatial analysis and predictive analytics. Tutorial from IU
Available to all Northwell Health staff and students of the ZSOM or the Elmezzi Graduate School of Molecular Medicine. Priority access provided for Residents, Fellows, GME Program Directors and Associate Directors, for individual or multi-user department access. Contact medicine.library@hofstra.edu for application form.
A versatile statistics tool purpose-built for scientists. Click here for an overview video.
Gephi (free)
A free software for network analysis, comprised of "nodes" and "edges". Guide here
Orange (free)
Free, open source data analysis and visualization with easy to construct visual "workflows." Guide here
Qiita (free)
Qiita (canonically pronounced cheetah) is an entirely open-source microbial study management platform. It allows users to keep track of multiple studies with multiple ‘omics data. Additionally, Qiita is capable of supporting multiple analytical pipelines through a 3rd-party plugin system, allowing the user to have a single entry point for all of their analyses. Tutorial here
SAS (Available to Northwell employees via the biostatistics unit for a fee. Contact biostatistics@northwell.edu.)
A command-driven software package used for statistical analysis and data visualization. SAS Tutorial by Dr. Dwight Galster
MATLAB (Available to current Hofstra students. See here.)
MATLAB is an application based on a scripting language specifically designed for expressing matrix and array mathematics. Try this introductory course from the Carpentries on MATLAB.
Python/Anaconda (free)
Anaconda is the most popular Python distribution and includes popular data science packages. Try this introductory course from the Carpentries on Python.
R is a free, open source software program for statistical analysis, based on the S language. RStudio is a free, open source IDE (integrated development environment) for R. (You must install R before you can install RStudio.) Try this introductory course from the Carpentries on R.
Fundamental algorithms for scientific computing in Python.
Arrays in Python.
pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool.
Network analysis
Machine learning and data mining
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
bqplot is a Grammar of Graphics-based interactive plotting framework for the Jupyter notebook.
Tools for processing natural language data
Creating data visualizations
Data manipulation and cleaning
Machine learning
Generates automated reports for documenting your code and preserving reproducibility
Collection of common data science packages
Robust package for data wrangling
See also this article with many more specialized data analysis packages.
Inspiration for data visualization in R.
Biostatistics for Radiologists by 
Biostatistics and Computer-Based Analysis of Health Data Using Stata by 
Biostatistics for Medical and Biomedical Practitioners by 
Basic & Clinical Biostatistics: Fifth Edition by 
Primer of Biostatistics by 
Medical Statistics by 
Modern Bayesian Statistics in Clinical Research by 
Introduction to Statistical Methods in Pathology by 
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