Project Details

Description

The Statistical Advisory Unit is run by statisticians in the Department of Mathematics.

We provide help and support on research activities in the Faculty of Science and Engineering when expertise in statistical modelling/data analysis is required.

The purpose is to enhance our research profile in terms of outreach and income.

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's finance 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 in the booking form (available under Access Project) and send it to statisticaladvisory.unit@manchester.ac.uk.

Our expertise

Madhuchhanda Bhattacharjee
Modelling and analysis of large/heterogeneous data using techniques from Bayesian/classical statistics and machine learning, with applications in bioinformatics, statistical genetics, epidemiology, spatial data, environmental data, engineering (reliability), medical (survival analysis) and econometrics.

Georgi Boshnakov
Exploratory data analysis, forecasting, graphics, multivariate analysis
numerical analysis and optimisation, probability, simulation, spatial statistics, statistical computing, statistical inference, time series.

Christiana Charalambous
Exploratory data analysis, GLMs and other non-linear models, longitudinal data analysis, simulation, statistical computing, survival analysis.

Ian Hall
Exploratory data analysis, visualisation of outputs, numerical analysis, operational research, probability, simulation, spatial statistics, statistical inference.

Yang Han
Simultaneous inference, multiple comparisons, personalised medicine, bioequivalence, clinical trials, analysis of longitudinal, multilevel and survival data, epidemiology of ageing and chronic disease.

Thomas House
Exploratory data analysis, network data, fitting complex models to data, prediction under uncertainty, Biostatistics, epidemiology, population health.

Peter Foster
Multivariate analysis, nonparametric statistics.

Saralees Nadarajah
Multivariate analysis, nonparametric statistics, probability distributions, reliability, sampling, simulation, statistical inference, time Series.

Olatunji Johnson
Geostatistical analysis, survey design, Biostatistics, disease mapping, joint modelling of multiple outcomes.

Theodore Papamarkou
Bayesian statistics, Bayesian deep learning, topological data analysis, topological deep learning, computing for healthcare and biomedical applications.

Timothy Waites
Design of experiments, Bayesian statistics, Computer experiments.

Jingsong Yuan
Spectral analysis, random fields, time series forecasting, GLMs and other nonlinear models, Pattern recognition and image analysis.


AcronymSAU
StatusNot started

Keywords

  • statistics

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