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The Cambridge University Statistics Clinic
Statistical Laboratory, |
Our service is back in Lent term! A detailed schedule can be found here!
Would you like to be reminded of the clinic meetings automatically? Then subscribe to our talks.cam feed!
We are group of people (mostly PhD students) working in and on Statistics and Machine Learning. We come from research groups all over town. This term, we will meet once every fortnight, in a room in the Centre for Mathematical Sciences and wait... for YOU!.
For those who have already visited us: We would be grateful if you could fill out our feedback form.
Are you a graduate student or academic staff at Cambridge? Does your work involve
- having to make quantitative statements about your data, including "error bars", the right size of which doesn't seem obvious at all?
- large amounts of data, full of difficult to express information?
- very limited, valuable, expensive data that you would like to make as much use of as possible?
- data generated by a complex process, not all of which is fully known, or some of which is of a stochastic nature?
- The control of a complex process, machine or system, the correct design of which is not entirely obvious?
Are you unsure how to proceed? Then maybe we can help.
We cannot do your (home)work for you, and we don't want to be a replacement for Wikipedia and Google. But if you come as well-prepared as you can, we may be able to
- help you understand how to formulate your problem in a more precise, abstract way
- show you contemporary, maybe cutting edge methods you can use to get more information out of your data, make more precise predictions, test your hypotheses more reliably, and control more complex systems
- point you to books, papers and software packages that might help you with your work
- get you in contact with other researchers in Cambridge and beyond, who specialise in your particular type of problem
Not much, really. Although data and data analysis are becoming more and more important, we think Statistics is often misunderstood or applied inappropriately. We are keen to hear about interesting problems from all sciences and to help you to get more out of your data. We hope that sometimes our discussions might evolve into genuine scientific collaboration, but in many cases a small acknowledgement in your paper of our assistance (if there is any) will be fine.
- We are in the computer laboratory and do not have a person like Richard...it is very difficult to find a solution when we hit the wall of the statistical problem...this clinic is great...30 minutes was a lot to us.
——— Dr Eiko Yoneki, Computer Laboratory
- I am very grateful to who respected my appointment and patiently explained to me some technical details of DPMCMC for nearly two hours.
——— Dr Audrey Fu, Department of Physiology, Development and Neuroscience
- Discussion was very useful and talking to you helped my understanding of my problem. Your suggestions were very useful and it has given me more confidence in my work. Excellent service that should be commended - it's very generous of you all to donate your time to the rest of the university.
——— Marc Stettler, Department of Engineering
- I have quite a collection of methodological and technical problems that could perhaps be advanced with the help of bright and creative statisticians. I will no doubt be back. It is extremely nice of you to provide your time - thank you statisticians!
——— Heather Battey, Department of Economics
- Thank you, what a great free service for us "lost" biologists to be able to more accurately understand our data and hopefully avoid wrong interpretations...
——— Dr Patricia Jusuf, Department of Physiology, Development and Neuroscience
The computing service training page http://training.csx.cam.ac.uk/ has courses on R, SPSS and Stata. They also sell SPSS at a discount price from their Software Sales.
Relevant statistics courses, which any member of the university can attend:
- Cambridge R User Group
- MRC Biostatistics Unit short courses
- Centre for Applied Medical Statistics short courses
- Part III Mathematics courses, in particular:
- Applied Statistics
- Applied Bayesian Statistics
- Graduate School of Life Sciences has a couple of courses, as well as a few useful links to other resources:
- The Joint Schools' Social Sciences MPhil Research Training course
Webpage maintainer: Yining Chen, Last update: Jan 2012