Analyzing

Data analysis refers to the process of inspecting, cleansing, transforming, and modeling data in order to identify patterns or extract meaningful insights. Methods of analysis tend to vary according to discipline and type of data collected but often include the use of algorithms, mathematical models, or software to manipulate and process the raw data. Since data analysis is the stage where new insights and knowledge are generated, it is important to document your tools and workflows so this process is reproducible by other researchers.

Considerations

  • Identify the most appropriate tools and methods of data analysis for your discipline or project
  • Document the methods, workflows, and tools used to analyze the data to support quality assurance and reproducibility
  • Consult the Rutgers Office of Advanced Research Computing regarding software and hardware requirements for storing and analyzing your research data
  • Consult with a librarian about data analysis training opportunities 

Resources

  • Rutgers Office of Advanced Research Computing ​
    Provides Rutgers researchers with essential computing, networking, storage, and data handling services, including the Clinical Research Data Warehouse (CRDW), REDCap secure data collection and management, Amarel high performance computing environment, and Research Data Storage (RDS) system.​
     
  • Rutgers Office of Statistical Consulting ​
    Data consulting services offered to Rutgers researchers via the School of Arts and Sciences in New Brunswick. 
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  • Rutgers University Biostatistics & Epidemiology Services (RUBIES) ​
    Data consulting services offered to Rutgers researchers via the School of Public Health.​
     
  • Data Science Guide ​
    The Libraries' workshops and consultations for data science, provided by librarians and graduate specialists​.
     
  • Open Science Framework ​
    Free, open-source tool to help researchers manage, store, and share research material (notes, code, data, preprints, etc.) throughout the research lifecycle.​
     
  • DataLad ​
    Free, open-source tool for data management, version control, and collaboration.​
     
  • LabArchives
    A secure, cloud-based electronic lab notebook (ELN) application enabling researchers to create, store, share, and manage their research data. Includes free and premium plans.
     
  • Sage Research Methods: Data Analysis and Interpretation
    An introduction to analyzing and interpreting research data.
     
  • Sage Research Methods: Datasets ​
    Master quantitative and qualitative data analysis with step-by-step guides and sample data.​