This is an HTML version of an attachment to the Freedom of Information request 'Experimental design training for PhD students'.

University of Edinburgh 
Enclosure 2: Mandatory training in experimental design and statistical analysis 
provided by the School of Biological Sciences 
 
The School of Biological Sciences does not provide mandatory training across the School as 
a whole, but some of the Doctoral Training Programmes do provide mandatory training in 
experimental design and statistical analysis, and the training is listed below by DTP. Apart 
from the MRC DTP in Precision Medicine, Biological Sciences students are registered at the 
University on one of our 6 PhD programmes depending on which institute they are affiliated 
to rather than a programme specific to their funding body. 
 
BBSRC funded EASTBIO Doctoral Training Programme 
Quantitative and Computational Skil s masterclasses – each conferring 10 training points as 
a requirement for EASTBIO students: 
Statistics and Experimental Design 
•  Basic concepts of statistics, summaries, standard error, p-values, confidence 
intervals and considerations in the design of experimental and observational studies, 
including sample size. 
•  Explaining study outcomes: the linear model, analysis of variance, confounding and 
adjustment. Recognising repeated measures and mixed models. 
Introduction to Matlab 
•  Basics, Math & Variables 
•  Logical Operators, Scripts, Functions and Flow Control 
•  Statistics and Plotting 
Artificial Intel igence and Machine Learning for Bioscientists 
•  Introduction to Machine Learning 
•  Focus on specific (statistical) machine learning methods 
•  Introduction to scRNA-seq and spatial transcriptomics 
•  Programming Activities in R 
 
Wellcome Trust funded programme in Hosts, Pathogens and Global Health 
Short introduction to statistics course (3 sessions), followed by a more detailed introduction 
to R course comprising of the following 7 sessions: 
•  Getting started in R 
•  Plotting data in R 
•  Introduction to Generalised Linear Models 
•  Advanced Generalised Linear Models 
•  Binomial and Poisson Generalised Linear Models 
•  Mixed Models 
•  Practical Problem  Solving 

University of Edinburgh 
Later in the year, topics covered are designing scientific questions, statistical sampling 
methods, basic experimental design for biologists, database design, and statistical analysis 
(choosing an appropriate statistical method, hypothesis testing, challenges in data analysis). 
Wellcome Trust funded programme in Integrated Cell Mechanisms 
The Introduction to Statistics workshop is run during induction week and is mandatory for all 
students.  The course covers: 
•  Basic probability 
•  Probability distributions 
•  Descriptive analytics (summary statistics, boxplots etc) 
•  Inferential statistics and hypothesis testing (population sampling, parametric and non-
parametric tests, p-values, multiple testing) 
•  Experimental design (power calculations, replicate experiments) 
This is followed up with a practical, which teaches programming, plotting and performing 
statistical tests in R. 
MRC Precision Medicine Doctoral Training Programme: 
During our introductory week which is mandatory, there is a session on Experimental 
Design/Research Integrity. We also have had an external provider for Research Integrity 
courses. Again, during mandatory Induction, we have a systematic review session which 
broaches methodological and statistical approaches, and we also discuss IAD courses with 
them, of which numerous are statistical. 
Finally, as it is an integrated PhD, we have 3 areas that they are required to pick taught 
courses from, one area is quantitative/ data skil s and includes many statistical based 
courses:  Introductory probability and statistics, Introduction to Bioinformatics, Medical 
informatics and Data Analysis, Introductory applied machine learning, and Quantitative 
genetics. 
NERC E4 Doctoral Training Programme: 
There are no mandatory training sessions in experimental design and statistical analysis; 
this would be part of the individual advanced training and arranged by the students 
themselves so it is tailored to their own needs.