1. Experimental Design and Efficient Research Dr. Richy Hetherington and Dr. Kim Pearce

2. Today’s Session Start a live experiment The scientific method in context You are the information generation Planning experiments Replication, randomisation and controls When sample size has to be small Simple tips for analysis The best help for you

3. An Experiment I’m going to hand some cards out take a one –Yellow for boys –Purple for girls –Write your 2D finger length 4D finger length Hand in the cards & we’ll Come back to this later

4. The Scientific Method in Context 1.Observe an interesting or puzzling phenomenon 2. Make a hypothesis to explain the phenomenon 3. Devise a test to see if your hypothesis is true 4. Carry out your test 5. analyse your results 6. State whether your hypothesis is correct if not at least have some information to help come up with a new hypothesis.

5. Take Home Messages no. 1 and 2 Leave no stone unturned (use all possible sources of information) Training to help (workshops throughout the year): Introduction to Library Facilities, Building robust search strategies - how to cover all the bases Evaluating electronic information - Sorting the wheat from the chaff Information Databases Advanced Medline Integrated Library and IT Skills Assimilation SDIs and Alerting Services Think about what is coming next

6. For Example: This workshop

7. Planning Your Experiments Take home message 3. Don’t believe everything you read See: Can I believe it (3 rd Feb) & Introduction to Critical Appraisal (online) Use non-rigorous experiments but be prepared to repeat them with rigour Take home message 4. Get as much help as is available in setting up your experiments (shy bairns get nowt!)

8. Make every result count Take home message 5. Set up your experiments so all eventualities are interesting Results can be meaningful and interesting without being statistically significant Also reporting non-significant findings avoids others from needlessly repeating that experiment

9. Get a statisticians help now “To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.” Dr. R. A. Fisher ca1938

10. Subject Selection and Randomisation Make sure the sample you take is representative of what you are testing Samples should be made randomly to avoid bias Double Blind Randomising means the researcher does not know which sample is being treated and which is the control

11. Replication Data from separate experiment should not be combined Datasets can be treated as replicates if all other variables are the same or weighted Analysis of replicates indicate the amount of variation in a result

12. Controls Control for everything you can Take as much care with controls as with samples Each experiment requires its own control

13. Where sample sizes need to be small Non-Human Primates often n=1 Animal experimentation

14. Analysis Software There are many statistics packages available. MINITAB & SPSS are the most widely used & among the most straightforward to learn. The ISS (computing service) provides support to users. Other packages may be used in various schools. Excel is not recommended as a piece of analysis software.

15. The Experiment Why 2D to 4D finger length ratio? –Many interesting characteristics attributed –Low ratios in men: sporty, musical, aggressive in women: more fertile –High ratios In men: better exam results In women: fertility

16. But are the gender differences real? Differences in the 2nd to 4th digit length ratio in humans reflect shifts along the common allometric line. Kratochvíl LKratochvíl L, Flegr J.Flegr J Biology Letters 2009

17. Summary First step is always plots & descriptive statistics Test should be kept as straightforward as possible as this makes interpretation/presentation of results easier. There is no reason to attempt complicated techniques when a simple test would work just as well

18. So what is right for you If you weren’t sure about anything mentioned here or you need refresher in stats – –ISRU very basic stats (45 minutes) –ISRU basic stats (3 hours) clinical / pure science Overview of Stats packages SPSS for beginners Advanced SPSS In your 2 nd year and you need a more thorough knowledge of medical stats- The medical stats course or the Statistical Methods course (Mres) One to one stats is useful for anyone at the right time Maths aid available daily in term time