Statistical Advisory Unit
The Statistical Advisory Unit provides help and support on research activities when expertise in statistical modeling or data analysis is required.
Description
What It Is
The Statistical Advisory Unit is run by statisticians in the Department of Mathematics.
We provide help and support on research activities when expertise in statistical modeling or data analysis is required.
How It Works
If we think we may be able to help after reviewing your request, we will contact you to arrange an initial meeting for half an hour or so to discuss the problem. If it is a straightforward case, we will be happy to give advice there and then. Otherwise, it is down to the individual adviser and yourself to come to an agreement as to the best way forward towards a solution, with help from the department office, if necessary, when contracts and fees are involved.
Bring a Statistician on Board
Statistical support, if required, should be budgeted for in grant applications, like computer officer time.
It is better to include a statistician as co-investigator if new methodology needs to be developed. An adviser may or may not be prepared to spend time working on a problem that is part of an existing grant.
Fees
There will likely be a fee payable for time spent beyond the initial free consultation. It will have to be agreed by all parties before the clock starts ticking, so feel free to come to us with queries. The adviser may decide to waive the fee in cases of collaborative research leading to publications as joint author and new grant applications as co-investigator. Any advice given for free will not carry any guarantee or warranties and a fee is no substitute for acknowledgement or co-authorship in publications.
Contact Us
Please fill out the booking form (see below under Booking Request Form) and send it to the [email to be provided here].
Our Expertise
Saralees Nadarajah
- Multivariate analysis
- Non-parametric statistics
- Probability Distributions
- Reliability
- Sampling
- Simulation
- Statistical inference
- Time Series