Skip to Main Content

Digital tools for research

Find information on digital tools to analyse and visualise data and text.

Introduction to statistical analysis

Data capture and analysis are core activities of the research data lifecycle. A number of tools are available to assist RMIT staff and students in the collection and transformation of data for their research projects.

See a selection of tools and applications listed below. This list is not exhaustive but represents a sample of tools commonly used by researchers.

To choose an appropriate software tool for analysing your data there are a number of criteria that need to be considered:

  • What do your supervisor and other researchers in your school or research area think about the appropriateness of the tool?
  • What functionality do you need to analyse your data and produce the output that you require?
  • Does the amount, complexity and type of data you have to analyse match the capacity of the software tool?

RMIT staff and students wanting further information on managing and storing data may also consult the library's Research Data Management guide.

Tools for statistical analysis







R Studio





For further information on NVivo, see this dedicated page.

Computing facilities and cloud based platforms

RMIT staff and HDR candidates can also apply for access to use high performance computing facilities and can also access cloud services for performing data analysis. Additional information can be obtained from the RMIT Researcher Portal.

High Performance Computing

More information on the RMIT High Performance Computing (HPC) facilities is available in this article.


RMIT is the first Australian university to implement a dedicated commercial cloud supercomputing facility - RACE (RMIT AWS Cloud Supercomputing) - by collaborating with Amazon Web Services (AWS) and AARNet. By combining the industry-leading cloud capabilities of AWS and the latest fibre network technologies from AARNet, RMIT is set to access tremendous connectivity and HPC processing power and provide seamless access to all our researchers, academics, students, and industry partners. RACE allows users to test ideas and solutions up to 100 times faster than existing on-site servers.

How To Access

The AWS cloud supercomputing hub plans to provide the following access schemes: 

1. Merit Allocation Scheme

This scheme will provide RMIT researchers with “free” access to AWS related services (e.g. EC2, S3) through a merit-based selection process. Please note: RMIT will need to pre-procurement a certain amount of AWS credits.  

2. Start-Up Scheme

This scheme will provide eligible RMIT PhD students and early career researchers with certain AWS credits. In addition, it will enable PhD students and early career researchers to evaluate the suitability of AWS cloud computing for their research and support them to apply for national competitive research grants (e.g. ARC and NHMRC).

3. Pay For Service Scheme

This scheme will enable RMIT staff to access AWS cloud services at a discounted rate. The AWS cloud supercomputing hub will also provide the relevant training, technical support, and expert services to lower the technical barrier for RMIT staff.  

For more detail about RACE, please contact Dr. Robert Shen at

More information called also be found on the RACE Sharepoint page and on RACE's public page, located at:


NeCTAR is a Cloud Computing Platform that provides flexible, scalable computing power to all Australian researchers. See further information on NeCTAR in the Research Data page of the RMIT Researcher Portal, under Analysing research data.

Further help and resources

There are other statistics courses within the university that current RMIT staff and research students can audit to help develop a foundation in statistics. With the course coordinator’s permission, you can access the course learning materials and attend classes. However, you will not be formally enrolled and will therefore not receive a formal grade. These courses run at undergraduate and postgraduate levels. Please contact the course coordinator for further information. The statistical consulting service recommends the following enabling courses: