Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Accept all cookies Reject all non-essential cookies Find out more

Experimental design and Statistics in Pre-clinical Research: the Good, the Bad and the Ugly

Research Skills

Friday, 29 November 2019, 9.30am to 5pm

Apply for this course

This full day classroom based MSD Skills training course is suitable for postgraduate research students and early career researchers wanting to understand the issues underpinning good experimental design, the bedrock of reproducible science.

COURSE AIM

This course aims to address some of the fundamental issues that are behind designing good experiments (focusing on pre-clinical experiments exclusively), the bedrock of reproducible science.

Arguably, all good experiments start with a good experimental design. Experimental design in the Biomedical Sciences is mostly about logic, common sense and the systematic application of relatively simple techniques to produce un-biased experimental results and reduce variation. This is good news because this should be relatively straightforward. Yet this is where the biggest blunders continue to be made, including by experienced biologists, with demonstrably expensive consequences on results.

The course will deal with those concepts, their links with statistical analyses generally and some of the traps that we have all fallen into. We will also address statistical issues relevant to animal research depending on the composition of the audience, in a session where the words 'enjoyment' and 'statistics' can hopefully share the same sentence.

COURSE FORMAT

A series of interactive lectures and scenarios delivered by Manuel Berdoy, BMS, Oxford.

COURSE CONTENT


At the end of the course, attendees should be able to:

  1. Describe some of the factors affecting reproducibility and external validity.
  2. List the different types of formal experimental designs (e.g. completely randomised, randomised block, repeated measures, Latin square and factorial experimental designs).
  3. Explain the concept of variability, its causes and methods of reducing it 
  4. Describe possible causes of bias and ways of alleviating it 
  5. Identify the experimental unit and recognise issues of non-independence (pseudo-replication). 
  6. Describe the six factors affecting significance, including the meaning of statistical power and 'p-values'.
  7. Identify formal ways of determining sample size. 
  8. Explain the fundamental principles behind the output of an ANOVA, including 'blocking' and 'interactions'.

COURSE LENGTH

One day

PARTICIPANT NUMBERS

Maximum 50 

 

*PLEASE BRING YOUR OWN LUNCH*

Booking Instructions

Step-by-step guidelines on how to book a Skills Training course.

How to book

Terms & Conditions

These terms and conditions apply to all MSD Skills training courses attendees.

Read the Terms & Conditions

Events from across the University

Research Practice e-learning courses are available to all research staff and students at the University. You can self-enrol at Research Practice Training.

Getting started: beginning your DPhil life in Oxford as you mean to go on – finding a work life balance and looking after your emotions, Getting on: managing professional relationships (supervisors, lab, peers), preparing emotionally for transfer of status, and dealing with DPhil crises along the way, Getting finished – preparing emotionally for submission, your viva, and life after the DPhil. To book visit Workshops and Groups | University Counselling Service

Department of Continuing Education offers Graduate School training programme is for Oxford University postgraduate students. For more details see here.