Dr Simon Blomberg is the Faculty of Science Statistical Consultant. He has a BSc (Hons) from Monash University, and a PhD from the University of Sydney, where his doctoral work was on population and behavioural ecology. His supervisor was Rick Shine. His career has included postdoctoral work here at UQ and QIMR, fauna survey consulting, honorary postdoctoral associate at the University of Aberdeen, and postdoctoral fellowships at the University of Wisconsin, Madison, and the University of California, Riverside. After returning to Australia, he was a visiting fellow at the School of Botany and Zoology, ANU, before completing a Masters Degree in Applied Statistics at the ANU in 2004. He then joined the ANU Centre for Resource and Environmental Studies as a level B statistician, before joining UQ BACS.
He has particular expertise in the analysis of data in ecology and evolutionary biology, but can be of help to staff and students in all the Faculty of Science schools and centres, in a wide range of data environments. Help is available for a wide array of statistica techniques, including the analysis and design of experiments, sampling design, computational statistics, exploration of complex multivariate data, survival analysis, time series, spatial data, genetic data, linear and nonlinear models, mixed effects models, the use of maximum likelihood and Bayesian methods, graphical analysis and presentation, simulation, and the application of stochastic processes.
His role is to provide statistical advice for students and staff across the entire faculty. However, he WILL NOT ANALYSE YOUR DATA FOR YOU! This especially applies to students. Basic proficiency with statistical analysis should be viewed as a necessary part of your training as a scientist. This is your best chance to learn. Please take advantage of it.
Simon is also available to supervise or co-supervise Honours or postgraduate students who have a substantial statistical aspect to their projects. He is also interested in developing collaborations with staff or students on major projects with a significant statistical component.
He recommends that staff and students obtain statistical advice in the planning stages of their research, to optimise resources, time, effort, and funds. Regular meetings throughout the lifetime of the project can be useful in addressing unforeseen changes to the study design, and the analysis of preliminary data. Consultations at the conclusion of the project can help with interpretation and presentation of the results.
Advice given during consultations is free and unconditional. However, if special work is necessary outside of consultations, then coauthorship of the resultant paper(s) is expected. Please discuss this with the Statistical Consultant at your first consultation.
The Statistical Consultant will not be held responsible for meeting or missing any of your deadlines. Your deadlines are your own problem. Be aware that analyses which you think should be straightforward can often contain hidden traps and difficulties which can take a considerable amount of time to overcome. Do not leave your analyses until the last minute.
The Statistical Consultant primarily uses and recommends R. http://www.r-project.org. If you use other software, then the Statistical Consultant can still offer advice on theory, but cannot be of much help in determining the correct command syntax/menu for your particular problem.
Consultation is by appointment 2.00 pm - 5.00 pm Monday – Friday
Room 116 Goddard Building (8)
Email (preferred): firstname.lastname@example.org
Phone 3365 2506
Finally, see the quote from a famous statistician, below:
The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.