On this page you will find answers to frequently asked questions about our applied statistics courses, separated according to whether they relate to 'payments and administration', 'course contents and learning materials' or 'other course details'.
1. Payments and Administration
- Can I cancel my place on a course (and get a refund)?
For delegates registered on any of our usual short courses, no refunds will be given for non-attendance or cancellations made within 5 working days of the start of the course.
For delegates registered on one of our summer schools, no refunds will be given for cancellations made within two weeks of the start date or for non-attendance. Cancellations made within two to four weeks of the start date will incur a fee of 25%.
For those on funded places (ICH/GOSH staff and doctoral students) on any course, cancelling after the deadline (or none/partial attendance) will incur a late cancellation fee (£100 for our five-day ‘Introduction to Research Methods and Statistics’ and £50 otherwise).
To cancel a place, please email firstname.lastname@example.org
- I am registered for a course and would like to swap for another date, is this possible?
Delegates wanting to swap their place for another date can do so free of charge, provided it is before the cancellation deadline (see above) and there is availability on the other course.
To swap a date, please email email@example.com
- What are the options for the organisation and payment of a group booking?
For larger group bookings, we can organise a bespoke course for you and your team or organise an extra date for one of our existing courses. Click here to enquire.
If you want to register more than one delegate for one of our existing dates, you may proceed with separate payments for each delegate by registering from one of our event pages (there are links from these pages to the UCL online store, where payment details can be entered). If you would like to check whether there is sufficient availability for all your team before registering, please email firstname.lastname@example.org. Alternatively, you may enquire about payment via invoice (only appropriate for large number of delegates).
- What are the payment options?
We recommend that UCL and non-UCL delegates register from one of our event pages that are accessible from the CASC homepage (there are links from these pages to the UCL online store, where payment details can be entered).
As per UCL regulations, we cannot accept Inter Departmental Transfers (eIDTs) for UCL staff. The UCL online payment system (UCL online store onlinestore.ucl.ac.uk) generates a receipt for all payments which could then be used for claiming course fees back.
For a large number of delegates, we may be able to organise payment via an invoice, in which case we would require a Purchase Order number.
- Do you offer any discounts?
Staff and doctoral students from ICH and GOSH: On most of our courses there are limited free places available for internal delegates. If this option is no longer available on the online store (i.e. all free places have been taken), you still qualify for the UCL discounted rate as follows.
Other UCL staff, students and alumni: You are entitled to a 50% discount for all courses apart from the summer schools. We are unable to offer discounts to members of other universities or hospitals.
Early bird discounts: Discounts for early bookings are available only for our two annual summer schools, but not for any of our other short courses.
For customers who don’t qualify for the ICH/GOSH free places, we operate a loyalty scheme entitling delegates to attend a course for free after collecting six course stamps. Short courses of up to two days are worth one stamp, our five-day ‘Introduction to Research Methods and Statistics’ course is worth three stamps. To take part in the loyalty scheme, speak to one of us during a course.
For details of fees, please see the course-specific web pages (accessible through our homepage).
2. Course Contents and Learning Materials
- Which course would you recommend for me?
“I have very little knowledge of statistics and want to get a good understanding of the basics…”
We recommend our five-day classroom-based introduction course (please see the course page for more details - Introduction to Research methods and Statistics). Alternatively, our two summer schools that run every year are also a good place to start (Introduction to Statistical Thinking and Data Analysis, and Introduction to Statistics and Regressions with R). The former summer school is a classroom-based course that focuses on the theory, or if you want something more practical/applied, you may prefer the latter computer-based summer school.
“I already have a basic knowledge of statistics (e.g. p-values, confidence intervals), where do I go from here?”
Whether you have attended one of our introductory courses (see above) or learnt the basics of statistics elsewhere, we recommend attending our Introduction to Regression course (a one day classroom-based course with an optional one day workshop using the software SPSS). Regression analysis is a very powerful statistical method that can be used to answer a wide range of research questions. Once you have a basic understanding of regression, then you can progress to one of our other advanced regression courses (Introduction to Logistic Regression, Introduction to Poisson Regression, Introduction to Survival/Time-to-Event Analysis, Overview of Regressions with R).
We also recommend having a good understanding of a statistical software package if you are running a data analysis (Introduction to SPSS, Introduction to R, Further Topics in R, and Introduction to Stata). See our other frequently asked question (which statistics software package do you recommend?) if you are not sure which one is most suitable for you.
Aside from the above mentioned courses, we offer many other statistics courses that are more ‘niche’ and may be relevant to your research (see the full list on our homepage).
- Which statistics software package do you recommend?
We run statistics courses in SPSS, Stata and R. We can’t give a single recommendation as each software package has its own merits, but here is a brief summary of each to help you decide:
SPSS: The easiest software package to learn because most functions can be performed through the drop-down menu. There is a programming language associated with SPSS, but it is not necessary for researchers doing basic statistics. The disadvantage is that SPSS is relatively inflexible, and may not have all the functions you require if you want to take your statistics beyond a basic level. To use SPSS on your own computer if you are not a staff member or student at UCL, you need to purchase a license. The license needs to be updated annually.
Stata: This is great for the researcher that wants a more flexible and powerful package than SPSS, but would rather not learn a ‘pure’ programming language such as R (see below). Stata has its own programming language for almost all types of data analysis. Stata also has a drop-down menu with fairly comprehensive list of options for various statistical methods. To use Stata on your own computer, you need to purchase your own license (including staff members and students at UCL).
R: This software package can do just about any analysis you like and is completely free to download, requiring no license. However, it is necessary to learn the R programming language and therefore has a steeper learning curve than SPSS and Stata. If you see yourself doing data analysis regularly in the future, this might be the best package for you.
- Can I purchase the materials without attending a course?
Yes, it is possible to purchase course materials without attending the course. All courses have extensive notes and often include slides, exercises, solutions and lecture recordings. To enquire please email email@example.com.
- Are any of your materials available online?
All the notes that accompany our ‘Introduction to Research Methods and Statistics’ course are available online here. This resource also contains additional material in the form of additional practical exercises with solutions and embedded links to excel sheets for calculations.
Spreadsheets are also available that accompany two of our courses that could help you with your analysis:
- Chi-square and Beyond for 2x2 Tables - spreadsheets available here
- Sample Size Estimation and Power Calculations with Excel - spreadsheets available here
These add-ons do not contain the full notes and should be used in conjunction with the course notes.
- Can you recommend any introductory statistics textbooks?
We recommend the following:
Practical Statistics for Medical Research, DG Altman, Chapman & Hall, 2006. ISBN 1584880392
Medical Statistics: A guide to data analysis and critical appraisal, J Peat & B Barton, BMJ Books, Blackwell Publishing, 2007. ISBN 978-0-7279-1812-3
Essential Medical Statistics, BR Kirkwood & JAC Sterne, Blackwell Science, 2005. ISBN 978-0-86542-871-3
Essential medical statistics. Betty R. Kirkwood, Blackwell Pub. 3rd. ed. 2012. ISBN: 9781405158961
An Introduction to Medical Statistics, M Bland, Oxford University Press, 2015. ISBN 9780199589920
Medical Statistics at a Glance, A Petrie & C Sabin, Wiley-Blackwell publishing, 2009. ISBN 9781405180511
Statistics with Confidence, DG Altman, D Machin, TN Bryant, MJ Gardner. BMJ books, 2005. ISBN 0 7279 1375 1
Presenting medical statistics from proposal to publication: A step-by-step guide. J Peacock & S Kerry, Oxford University Press, 2007. ISBN 0-19-859966-8
Medical Statistics: A textbook for the health sciences. D Machin, MJ Campbell & SJ Walters. Wiley & sons, 2007. ISBN 978-0-470-02519-2
Medical statistics made easy. Michael Harris et al. Banbury, England, Scion, 2014. ISBN 9781907904035
Discovering statistics using SPSS. Andy Field, Sage Publications Ltd, 2009. ISBN 978-1847879073
An adventure in statistics: the reality enigma. Andy Field, SAGE Publications Ltd, 2016. ISBN 9781446210451
Discovering Statistics Using R. Andy Field, Jeremy Miles and Zoë Field, Sage Publication Ltd, 2012. ISBN 978-1446200469
Oxford Handbook of Medical Statistics - Oxford Medical Publications. Janet Peacock, Philip Peacock, Oxford University Press, 2010. ISBN 9780199551286
The Cambridge Dictionary of Statistics in the Medical Sciences. Brian Everitt, Cambridge University Press, 2011. ISBN: 9780521479288.
Statistical Principles for the Design of Experiments. Roger Mead et al., Cambridge University Press, 2012. ISBN 9780521862141
3. Other Course Details (not related to the content)
- Can I receive a certificate for attending a course?
Certificates can be arranged by emailing firstname.lastname@example.org. An electronic pdf certificate will be emailed to you after the course upon confirmation of attendance.
- Are your courses certified for Continuing Professional Development (CPD)?
At present the courses we run are not externally certified for Continuing Professional Development. We can provide a UCL Certificate of Participation that can be used to evidence CPD hours.
- I am attending one of your courses, how should I prepare?
Electronic notes will be provided on the Moodle page (access details will be emailed to you shortly before the course), which we recommend you either print or have open ready for the start of the course. Other electronic materials such as presentation slides may also be available depending on the specific course.
Most courses also require a means for taking notes (either electronically or using a pen/paper if you prefer) and access to a basic calculator. If you have a smart phone/tablet/laptop, a standard calculator application should be sufficient.
On computer courses, delegates must install and license any necessary software before arrival.