Thing 9: Statistical Analysis Software

Image: “How online communities function” by Amber Case via Flickr (CC BY-NC 2.0)

This week’s post will help you to learn about a selection of different statistical packages, how to access them (on campus and outside the university) and where to get help.

Getting Started

Statistical analysis is an integral part of evaluating research data and presenting results in any research field. There is a broad range of software packages available that facilitate this. Some are freely available from the internet, but most of the advanced and more comprehensive statistical software are available only as commercial packages.

The more popular statistical packages among the university community are listed in the table below.

Choosing which package to use:

Not all the software packages do every type of analysis. Some packages are very powerful and flexible, hence can perform a wide variety of statistical analysis. In contrast, others have specialised functions like creating graphs, sample size calculations, genetic analyses etc. Therefore, your choice of a statistical package will depend on the nature of your research and the type of analysis you will be doing. Factors to be considered when choosing the right statistical tool for your particular research:

  • The number, size and complexity of data sets you have to be analyzed, and the capacity of the package.
  • The functionality and the output you require.
  • Packages used by others in your department and/or others doing similar research.
  • What is currently available at the University of Melbourne, or what can be purchased through your department.


Main Features Considerations Availability at University of Melbourne
NVivo Designed for qualitative research with rich text-based and/or multimedia information. Intended to assist researchers to organize and analyze non-numerical unstructured data. Used mainly in social sciences and marketing
  • Coding necessary to identify patterns and theories in research material which can be time-consuming.
  • Currently installed on Library computers.
  • May also be available in some Faculty Labs.
SPSS Primarily for statistical analysis. Especially useful for analyzing large-scale survey data.
  • Absence of robust methods (e.g. Least Absolute Deviation Regression, Quantile Regression, …)
  • Available to all students via myUniApps.
  • Copies of the installation discs (for Windows) are available for loan from the service desk at the ERC Library.

Minitab is a command- and menu-driven software package for statistical analysis. Analysis can be performed using drop-down menus or syntax.

Support for design and analysis of experiments (including factorial, response surface, mixture, and Taguchi designs).

  • No Mac OS operating system support.
  • Range of statistical analyses is not as wide as in other packages such as SPSS and SAS.
  • Available to all UoM students via myUniApps.
  • All library and Student IT labs.
  • Some Faculty Labs and at the Graduate Centre (1888 building).

SAS (Statistical Analysis System).

In addition to statistical analysis, it also allows programmers to perform report writing, graphics, business planning, forecasting, quality improvement, project management and more.

  • Graphics can be cumbersome.
  • Reportedly extensive lag times for the implementation of new methods.
  • Documentation and books tend to be very technical.
  • Available to all students via myUniApps.
  • All Library and StudentIT labs. Some Faculty Labs
  • Some students may be eligible to download SAS via the Virtual Lab
  • SAS 9.4 installation discs are available for loan from the ERC service desk; program files available on USB which can be borrowed from the IT help desk at ERC Library.

MATLAB is intended primarily for numerical computing.

MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, the creation of user interfaces, and interfacing with programs written in other languages, including C, C++, C#, Java, Fortran and Python.

It is primarily used in the fields of engineering, science, and mathematical economics.

  • Lacks implementation of some advanced statistical methods.
  • Integrates easily with some languages such as C, but not others, such as Python.
  • Limited GIS capabilities
  • Available to all students via myUniApps.
  • All Library and StudentIT labs. Some Faculty Labs
  • Some students may be eligible to download the software via the Virtual Lab

Genstat is used in a number of research areas, primarily in agriculture, biology, genetics, ecology, environment (forestry and soil), food science and medical and pharmaceutical. But it is also used in finance, industry, engineering, statistics, and mathematics.

For those with more technical knowledge, it offers more power and flexibility through a command language interface.

  • The University of Melbourne holds a site license for GenStat which enables all staff and students to use the program on University-owned computers.
STATA  STATA is a general-purpose statistical software package used primarily in the fields of economics, sociology, political science, biomedicine, and epidemiology.
Its capabilities include data management, statistical analysis, graphics, simulations, regression, and custom programming.STATA uses a point-and-click interface as well as command syntax.
  • Can only hold one dataset in memory at a time.
  • Cannot handle very large datasets – may have to sacrifice the number of variables for the number of observations.
  • Graphs have limited flexibility.
  • Stata is available to Faculty of Business and Economics students on or off campus via myUniApps.
  • Staff may request installation on University-owned computers.

R provides access to a variety of statistical and graphical techniques including linear and non-linear modelling, classical statistical tests, time-series analysis, classification, and clustering.

Functionally, the program is considered comparable to SAS.

However, R has the advantage of being open-source and thus freely available.

  • Large online help community but no ‘formal’ tech support.
  • Have to have a good understanding of different data types.
  • Many user-written packages may be hard to sift through.
  • R can be downloaded from the publisher’s website
  • Additional enhancements of R have been created by RStudio. RStudio is accessible via MyUniApps.
  • R for Windows is installed on all Library computers.

Try This

Have a look at the MIT Library Guide for statistical packages. Compare the strengths and weaknesses of the statistical packages they list. Does that help you in choosing one that will best fit your research?

Also look at UCLA’s Institute for Digital Research and Education (IDRE) website.  Under the ‘software‘ tab you can read about the features of some statistical packages. Look especially at the information under ‘Statistical Analysis‘ that goes into detail about the statistical features of each software.

Learn More

University of Melbourne Library Guides

Need help with a stats issue or want some training?

Training and support options for University of Melbourne students and staff

  • The Statistical Consulting Centre provides a range of services to the University of Melbourne academic community.
    • The Melbourne Statistical Consulting Platform (MSCP) provides advice on statistical methods to graduate researchers and staff from any discipline across the university.
    • Consultants can provide one-on-one advice to assist with any stage of a quantitative research project from planning and data collection to analysis and reporting.
    • The MSCP deliver short courses in statistical methods in collaboration with the Statistical Consulting Centre.
  • The Graduate Students Association
    • offers a number short courses including for NVivo throughout the year.
  • Facebook group for R users
  • The Research Platform Services team has a new help desk service for researchers, by researchers.
    • The Help Desk is located on level 3, Eastern Resource Centre Foyer – adjacent to the ERC Library. Regular hours yet to be advised, however, it is open on Monday 18 September from 10.00am – 3.00pm and on Thursday 21 September from 11.00am – 3.00pm. 
    • Researchers are welcome to drop in at any time to get help and support, including free training and advice on tools such as R and R Studio, Matlab, Python, Omeka as well as Data storage, HPC and compute.
    • Contact Research Platform Services for more information.
  • The Social and Cultural Informatics Platform (SCIP) supports the investigation, development, and use of advanced research tools to analyse or visualise data and information in different forms. SCIP offers training and support consultations to all University researchers and collaborators. More information or contact SCIP. 

Other free statistical software packages and resources

This post was written by Dr. Harshanie Habarakadage (Library Cadet, Brownless Biomedical Library) and Guido Tresoldi (Liaison Librarian – Science and Engineering)

Leave a Reply

Your email address will not be published. Required fields are marked *