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Data Science: DATA ANALYSIS

Data Science Subject Guide

Online Research Tools

Researchers may find the following tools useful in their work. Emphasis is given to free (or at least having free components) and online tools or services.

Electronic Lab Notebook
Information for researchers who are interested in adopting an Electronic Lab Notebook system for documenting research and managing data.

RSpace
An ELN for researchers to organize, manage and collaborate on their projects.

Hivebench
Biology-focused experiment, lab and project management.

Docollab
Project management system, collaboration.

Benchling
Life Sciences focused experiment, lab and project management.

Statistical Software

The Map and Data Lab located on the main floor of the library includes 16 workstations, equipped with ArcGIS software, that support the three major statistical software packages- SAS, SPSS, and NVIVO through Ryerson Virtual Applications.

Data Analysis Packages

Below are descriptions for each package to help you decide which to use. Note that if you have data in SAS format, for example, but prefer to use Stata (or SPSS), then you are not stuck using SAS. You can use StatTransfer to convert the SAS data into Stata.

  • Stata: Stata is a relatively (compared to SAS and SPSS) easy to learn package which give you a choice among a command-line interface, syntax or program file (called a "do-file" in Stata), and pull-down, fill-in-the-blank GUI interface. Stata is very good with time-series data and has many survival analysis routines. Stata also gives you the ability to program your own commands. One drawback to Stata is that it loads the entire dataset into memory, so if your dataset is very large, you may not be able to use Stata. This is a relatively rare occurrence, however. Generally, if you have little or no experience with any statistical package, Stata is probably your best choice.

  • SPSS: SPSS is another very popular statistical package. It has probably the best GUI interface of the three packages, as well as the ability to write programs. Like SAS, you can probably do everything you will ever need to in SPSS. You can do most of your work in the GUI, but not all, so you may need to learn how to program in SPSS. Like SAS, programming in SPSS has a pretty steep learning curve.
  • NVIVO: NVivo is the most used qualitative and mixed-methods data analysis software tool by academics and professional researchers globally. NVIVO is ideal for complex research projects, whether you’re working solo or in a team. This application assists in the management, analysis, and organization of text (interview and focus group transcripts), images, and sound files and is appropriate for those engaged in a diverse range of qualitative research methods.

Data Mining