The Quantitative Consulting Unit (QCU) is part of the Research Office at Charles Sturt University that provides statistical support to research students and staff across the University.

QCU's core statistics support services include:

    General consultancy on statistical theory and application related to research problems

    Tutorials/training for learning and using analysis software such as R, SPSS, G*Power3.1, @Risk and Netica

    Advice on, support to, and completion of statistical analysis needed from research projects

    Workshops for HDR students and researchers to enhance their statistical skills in special topics such as design and analysis of experiment, statistical graphics, and Bayesian Networks.

Through the QCU research Honours, Masters and PhD students are offered a free initial consultation to provide a kick-start to their research to ensure that they embark on a path that will lead to successful completion of their research.  Subject to the terms and conditions specified in QCU's service policy, further assistance is available to meet various needs for statistics support throughout the whole process of their research studies.  CSU staff researchers are also entitled receiving QCU's statistics support services as detailed in our service policy.

The QCU also runs statistics workshops/tutorials - if you are a CSU student or staff member doing research and wishing to update your quantitative statistical skills, these workshops/tutorials could be just what you need. If you are external to CSU you are welcome to attend, to register your interest in our workshops, please email the QCU Administrator - qcu@csu.edu.au **Please note ** this email address is only manned on Monday and Friday)

John Xie - John is experienced in Statistical Data Analysis and Bayesian Network.  If you would like to know more about John's background.

*** Latest News***

Moving to a World Beyond “p < 0.05” -  important changes may happen for future statistical analysis practice in scientific research - a message from Quantitative Consulting Unit. Click here for more information.

Without referring to statistical significance in presenting our data analysis results, how could or what should we do? Here are three excellent references (an article published in 1996 by Nester; a book chapter published in 1997 by Schmidt and Hunter); a 30-min online video https://www.youtube.com/watch?v=iJ4kqk3V8jQ presented by Professor Geoff Cumming that we would like to recommend for your information.

Mid Monthly Meeting

Our next mid-month R tutorial online Q & A session will be held on August 11, 2020 from 2-5pm.

A three-hour mid-month R tutorial online Q & A session will be run between the monthly PD sessions to help beginner R users who have any questions relating to their research project answered.

If you would like to participate in these session please use the following Adobe Connect link https://connect.csu.edu.au/r_qandasession/ to enter. This will be the link for every Q & A session.

cRow meeting

It has been decided that the cRow meetings will no longer be held.  This is due to the QCU being offered the opportunity to run the R tutorials through the Research Office's Professional Development Calendar Program. These PD online sessions are open to all CSU staff and students, if you wish to participate in these R Tutorials please contact the QCU for further details or alternatively keep an eye on the Research Office Professional Development Calendar  Or refer to the Research Hub Web Page.

R tutorial resource materials have now been added to our web page under the resources tab. Please note you will need to have CSU login privileges to access this folder. if you do not have a CSU login please contact the QCU for assistance.

Thomas Williams will be holding some R meetings throughout the year for beginners or people who are new to the R statistical program. I will be posting meeting times and location here to help Thom with getting numbers to these meetings.

Bayesian Network workshops

Bayesian Network (BN) is an intuitive, graphical representation of a joint probability distribution of a set of random variables with a possible mutual causal relationship. BN is a machine-learning data analysis technique and BN modelling approach complements the traditional statistical data analysis approach in overcoming the curse of dimensionality and naturally capturing the independence and dependence relationships among model variables.  Netica is the most widely used BN software in the world. If you can use Microsoft Word and Excel confidently in your work, you will be able to learn Bayesian Networks using Netica.  It is the conditional probability and hierarchical structure matter in modelling a complex real life problem and BN is one of the most suitable and powerful tools to do it. This 90-minute presentation will (intends to) cover the following topics:

  • Concepts and definitions about what is a Bayesian Network (BN); a very brief introduction to the theoretical basis of a BN model.
  • Demonstration of various BN applications through 10 examples (from the simplest toy example to some examples which are based on real life data sets) using Netica.
  • An overview introduction to a 3-day workshop on Learning BNs by Hands-on Practice with Examples.

A 3-day workshop (Wagga campus) on learning and application of Bayesian Network models (Bayes net and decision net models, and Dynamic Bayesian Network models) is available now: the workshop is designed/developed for maximizing the hands-on experiences in learning BNs from examples and keep the theoretical preliminary requirements / theoretical exposition to the minimum.   The goal is to establish participants’ ability to build BN models for solving the problems from their research or professional activities.

This is a fee-based workshop. For the workshop that is run on Wagga campus, Cost: $300 (including GST) per person for CSU student and staff, or DPI staff; $1,200 (including GST) per person for other participants (including morning tea, light lunch, and afternoon tea each day). For logistics reason, the workshop run on other campuses will be slightly modified to a 2.5-day workshop.  Cost: $200 (including GST) per person for CSU student and staff, or DPI staff; $800 (including GST) per person for other participants (morning tea, light lunch, and afternoon tea will be provided for the first two days; morning tea only for the third day).

Introduction to R Workshop

A three-hour workshop for a brief overview on data analysis using R

R is a free available professional statistical analysis software.  It is likely true that R is now the most popular statistical analysis software used by researchers at all levels all over the world.  More and more people are reporting their research results in the context of R in literature (e.g., professional journal articles, books, and workshop/conference presentations, etc.)  Different from the point-and-click (i.e., dropdown menu) type of the user interface statistical analysis software (such as SPSS), however, R is essentially designed for conducting analysis through inputting R scripts or command lines in the console window so that users are in full control what you are intended to do.  One of the very strength of R is in its graphical functionalities.  For various reasons, R is much less familiar or intentionally avoided by many non-statistician professionals who are not used to conducting data analysis by programming (i.e., writing command lines). This workshop first provides a brief overview on what is R and how to use R for statistical data analysis. After a brief account on the main features of R software, it is showed how to conduct statistical analyses via copy-and-paste of the R scripts into the R console window.  Various types of simple/specific analysis examples of using R are presented.   The second part of the workshop provides the information on what support is available from the Quantitative Consulting Unit (QCU) to researchers at CSU for learning/using R and offers the opportunity for the presenter to answer participants’ questions on how to learn R. This workshop is developed for promoting data analysis using R by targeting those ones who have little or no experience with R but do have basic understanding of statistics at year one undergraduate level and/or experiences of performing data analysis using other software.  If you are a confident SPSS user, you should find this workshop interesting and comprehensible.

Structure of the workshop:

1.5 hours: a very brief overview of what is R and an introduction to how to use R for statistical data analysis (mostly descriptive data analysis but with many graphs)

Morning tea break or lunch break (depending on the starting time)

1 hour:

  • what support is available from QCU to researchers at CSU for learning/using R
  • the very basic points on how to learn R

This is a fee-based workshop to ensure the people who registered for the workshop will commit himself/herself in their time and efforts for participation.  The registration fee is $50 per person and the cost of a working lunch is included. Five people is the minimum number required for running one of this workshop.  In most cases we are flexible to suit the need of the majority of the participants in terms of their preferred time and place (e.g., we are happy to travel to different campuses) for the workshop.  The workshop resource materials are available to participants only in electronic form (i.e., you can/need to download them onto your computer). If you are interested in holding or attending any of these workshops please contact cmoffat@csu.edu.au we can also conduct workshops online.

G*Power workshop

The main purpose underlying statistical power analysis is to help the researchers to determine the smallest sample size that is suitable to detect the effect of a given test at the desired level of significance.  Developed at the Institute for Experimental Psychology in Dusseldorf Germany, the free software G*Power was designed as a general stand-alone power analysis program for statistical tests commonly used in disciplines such as agriculture, animal studies, health science, social and behavioral research, etc.  Power analysis is often intentionally or unintentionally ignored because it involves several statistical concepts which may not be necessarily straight forward to understand and the power analysis formula is very model specific.  G*Power provides an effective and very user-friendly solution for promoting the application of power analysis as part of the routine statistical data analysis procedure.  It offers a wide variety of calculations related to power analysis along with graphics and protocol statement outputs.  The actual teaching and learning time is five hours divided into three sessions.  The workshop program details are as follows.

  • 9:30am – 10am: registration and morning tea
  • 10am – 12pm: learning and practice session 1 – attendees install the GPower software onto their laptop computers; basic concepts of statistical power analysis will be introduced; a first touch with GPower; apply GPower to perform power analysis for five different statistical models.
  • 12pm – 1pm: the lunch hour
  • 1pm – 2:30pm: learning and practice session 2 – attendees continue to learn and practice power analysis using GPower for six more statistical models including the ANOVA model with more than two categorical factors.
  • 2:30pm – 3pm: afternoon tea break
  • 3pm - 4:30pm: learning and practice session 3 – attendees continue to learn and practice power analysis using GPower for five more statistical models including a simple repeated measure regression model case.
  • 4:30pm: close of the workshop

The GPower user manual (both the hard copy and the electronic copy) will be prepared for the attendees for the workshop.

Quantitative Consulting Unit (QCU) runs this one-day hands-on practice workshop for learning power analysis using GPower 3.1 from time to time based on the request from the researchers (HDR students and staff members) at CSU. It is a fee-based workshop for the purpose that anyone who would register and pay for the workshop is most likely to commit him/her time and effort for the expected learning outcomes. This is a fact-to-face workshop and we will run the workshop as sketched above with minimum two confirmed attendees. The upper limit of the number of attendees for each workshop is 10 for a better learning and practice result.  We are flexible in running this one-day workshop multiple times and on different campus as long as the demand requires.

Please send us your Expression of Interest by email: qcu@csu.edu.au or talking to us about your request by phone: 02-69332223 (Coral) or 02-69332229 (John).

Modified QCU service Policy

(Effective 1st September 2017)

QCU provides a free (30-minute session) initial consultation service which may lead to

1.Further paid consultation services - $150 per hour (if necessary an extra free (30-min.) consultation session is available for further confirming the terms and conditions of the consulting services)


2. Further free collaboration services (subject to an upper limit of the service hours allocated for each case) requiring co-authorship/ownership of research publications/outcomes if the contribution of the consultation service is substantial.

  • A time limit (per case) available for the free services will be as follows:

10 hours for honours and masters students;

20 hours for doctoral candidate students;

20 hours for staff members.

Service priority will be applied in the order of:

Masters by research and Doctoral students (first priority);

Staff members (second priority); and

Masters by course and Honours students (third priority).

  • Any consultation time which exceeds the limit may be charged at $75 per hour unless an exemption is granted by the Research Office (subject to the availability of QCU's consulting resources).

Only the time directly related to the consulting services is counted as 'consulting hours' – for example, the time spent with the client in phone-call or email communications or in face-to-face meetings, and time spent on performing data treatment and/or analysis and/or presenting the analysis outcomes; time spent on background reading, finding reference materials or familiarisation with or learning specific topics related to the consulting problem normally will not be counted.

  1. Understanding and defining the research problem(s) qualitatively and quantitatively so that relevant information/data are collected and analysed using the most suitable analysis methodology are essential for students at all levels.   The use of QCU's services (free or paid) should not become an excuse for students not being able to understand and/or interpret their research outcomes/findings – if so, this may seriously compromise the integrity of their academic assessment outcomes.  Therefore, under their supervisor's guidance, students should try their best to build up their own ability in performing valid data analyses and correctly interpreting their analysis results with the help of QCU's services.

LaTeX Users Group (LUG)

LaTeX is a free powerful open source document preparation system that is widely used amongst the scientific research community.

Due to the low interest shown in this group, LaTeX will now consist of a direct contact service. If you would like some assistance/help with LaTeX please contact John directly on 02 6933 2229 or email gxie@csu.edu.au.  if you would like to be kept informed regarding this group please email cmoffat@csu.edu.au


Workshops and tutorials:

  • Free monthly online R tutorials are held through the Research Office Personal Development Calendar for 2020 (March to December: total 10 tutorials)
  • Free mid-month R tutorial online Q & A sessions as the follow-up supportive tutorials for the above PD program online R tutorials (2020 March to December); see the Mid Monthly Meeting section above for more details.
  • The fee-based half-day R Introductory workshop
  • The fee-based workshop on statistical power analysis using G*Power
  • The fee-based workshop on learning Bayesian Networks by hands-on practice with examples using Netica
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