Multiple tools are available to assist in data analysis. Below are best practices and tools that can be used for statistical analysis and visualization of data.

Best Practices

DataONE provides multiple best practice guidelines to help in the analysis of data, including considerations on the compatibility of any data that is being integrated, the description of methods to create derived data products, the documentation of steps used in data processing, and identifying outliers, among other analysis topics.

Data Output, Statistical Analysis, and Visualization

The Tulane Business Intelligence and Analytics (BIA) Team supports the University's business intelligence, business analytics, advanced analytics, data warehousing, data integration, self-service analytics, and enterprise planning practice areas, in addition to maintaining the University's data warehouses and various reporting sources and processes.

Numerous open source and proprietary software packages exist to help with data analysis and visualization. See Technology Services for a complete list of software licensed by Tulane University.

  • R is a free language and environment (R can also be described as open source statistical software) that is available for statistical computing and graphics. Downloads are available for Windows, MacOS, and a variety of UNIX platforms.
  • STATA is a complete, integrated statistical software package that provides everything you need for data analysis, data management, and graphics, produced by StataCorp.
  • SAS is a software suite developed by SAS Institute for advanced analytics, business intelligence, data management, and predictive analytics.
  • SPSS is a software package used for statistical analysis popular in fields including the health sciences and marketing.
  • ArcGIS is a comprehensive set of tools for compiling, visualizing, analyzing, editing, managing, and sharing geographic data. For more information about ArcGIS see the GIS research guide.
  • PolicyMap is a data and mapping tool that enables government, commercial, non-profit and academic institutions to access data about communities and markets across the US. Learn more about PolicyMap with the GIS research guide.
  • NCBI Data Analysis Tools allow researchers to manipulate, align, visualize, and evaluate biological data. Analysis tools are broken down into categories: Literature, Health, Genomes, Genes, Proteins, and Chemicals.
  • SankeyBuilder allows you to automatically build a Sankey diagram. Both free and paid accounts are available online.

Additional tools are available to assist with digital scholarship. See the digital scholarship webpage and research guide for more information.

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