Statistics for Graduate Biologists Course (School of Biological Sciences)

This course is designed to help graduate biologists acquire the statistical skills necessary for research projects and evaluation of the scientific literature. It provides practice in performing common statistical analyses.

• Postgraduates in the School of Biological Sciences
• Further details regarding Graduate School of Life Sciences' eligibility criteria are available

Details on the course content can be found online.

Lecture

• Samples and populations; the normal distribution
• The binomial distribution; testing hypotheses
• The t distribution
• Comparison of two independent, approximately normally distributed samples
• One-way analysis of variance (ANOVA)
• Analysis of variance (continued)
• Association
• Analysis of variance; models and factorial designs
• Techniques for non-normal data; non-parametric statistics
• Further aspects of regression and multivariate methods

Practical

• Introduction to the software
• Distributions
• Comparison of two samples
• Analysis of variance
• Association
• Regression models
• Factorial and nested analyses of variance

• To be able to perform simple statistical analyses based on the ideas discussed in the lecture
• To be able to devise and analyse simple experimental designs independently
• To be able to design experiments and surveys, and analyse your data correctly, on the basis of specialist advice, for more complex statistical problems

Presentations and practicals

• It is suggested that, soon after each lecture, you spend one hour going over the material in it. The amount of subsequent private study will depend on your background and your field of interest.
• Two hours’ revision of the material in each practical is suggested. The practical exercises and computers are available throughout the year, so there is plenty of opportunity to acquire the biometrical skills that you need.
• The course material is covered by many books and you may wish to refer to several to get alternative viewpoints.
• The reading list (and further details on the course) can be viewed online. Two books are especially recommended: that by Hinton assumes no previous acquaintance with statistics; that by Dytham focuses on the practical aspects of computer data analysis.

• Ten sessions of one hour
• Seven practicals of two hours

Yearly