Overview

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 November 5, 2020 from 2-4pm.

A two-hour 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.

Participants are able to attend an online Zoom meeting hosted by John by clicking the following link (just pop in, no appointment required): https://charlessturt.zoom.us/j/9110528730 .

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 workshop

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.

Workshop details can be found here

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.

Workshop details can be found here

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.

Workshop details can be found here.

Rasch Model workshop

This workshop is designed to meet the needs of those researchers whose research involves measurement and assessment/test of human performance and/or attitude.   The relevant research questions include: What is the best way to measure a person’s response (e.g., in terms of achievement performance or attitude on a latent (construct) variable)?  How good is a test instrument (e.g., reliability, validity, goodness-of-fit to a fitted (e.g., a Rasch) model)?  Therefore, researchers in education, health, and the social sciences disciplines are considered as the targeted potential participants. It is anticipated that this workshop would last for two days for participants who are familiar with statistical data analysis using R.  An extra day may be needed for participants who do not have experience of using

Workshop details can be found here

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)

OR

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).

3.   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.

4.  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

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.
  • Fee-based half-day R Introductory workshop
  • Fee-based workshop on statistical power analysis using G*Power
  • Fee-based workshop on learning Bayesian Networks by hands-on practice with examples using Netica.
  • Fee-based Rasch Model Workshop. A workshop of Rasch Model using R.
Quick Links
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