MSc Biochemistry

Fees for entry in 2027 have not yet been set. For reference, the fees for the academic year beginning September 2026 were as follows:

• MSc (full-time)
  UK students (per annum): £15,800
  International, including EU, students (per annum): £37,800

The fees quoted above are fully inclusive of tuition, administration and computational costs.

Fees for entry are subject to yearly review. The University reserves the right to increase your tuition fee by up to 7% each year for courses lasting more than one year, including to reflect rising costs associated with delivering our educational and wider student experience. Postgraduate fees information .

Always contact the admissions team if you are unsure which fee applies to your qualification award and method of attendance.

International student CAS deposit

Self-funded international applicants are required to pay a deposit of £2500 towards their tuition fees before a confirmation of acceptance for studies (CAS) is issued. Some applicants will be required to pay a higher deposit. More information on tuition fee deposits .

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

For the latest scholarship and bursary information please visit the fees and funding page .

International scholarships

Scholarships for international students are available through the Global Futures scheme. Visit the scholarship page to find out more about eligibility and how to apply.

An essential part of training as a biologist is to learn to design experiments and analyse and interpret data correctly.  The unit introduces students to data handling, presentation and statistical data analysis, and in the light of the requirements for a good statistical analysis lays the foundations for good experimental design and critical analysis of research.

The unit aims to introduce students to the methods and tools used in statistical data analysis and the procedures and tools used in the design of experiments.

Students will learn to handle, present and analyse data, to design experiments and understand the limits of experimental evidence. More specifically students will learn to:

• Test hypotheses and assess the statistical significance of results.
• Handle data, and the best use of graphics and descriptive statistics.
• Analyse biological data using classical statistical tests.
• Analyse data using R.
• Design successful experiments.
• Critically assess basic experimental designs and analyses in the literature.

Statistical Data Analysis:

Data and graphics using R

• Overview of statistics and hypothesis testing, types of data and graphs, descriptive statistics, basics of R statistical programming language.

Probability and statistics

• Probability distributions, Confidence intervals, Bootstraps, Hypothesis testing using a one-sample distribution.

Classical statistical tests

• Parametric and non-parametric tests to compare variances, means, proportions and counts in contingency tables. Covariance, parametric and non-parametric correlation.

Regression

• Estimating slope and intercept, statistical significance of regression, regression in R, model assumptions, model checking, and transformation.

Analysis of variance

• One-way, two-way and factorial anova, model simplification, model assumptions and pseudoreplication.

Experimental design:

• This unit provides students with a foundation in experimental design to ensure that they can design effective and efficient experiments. The topics covered include; standardization, sample size, hypothesis testing, experimental units, controls, replication, randomization, independence, pseudoreplication, covariates and power analysis as applied to basic statistical tests.

Delivery and assessment will be through lectures, workshops, group discussions and e-learning. Students will participate in computer practical sessions, and submit a plan for the experimental design and analysis of their current research project.

Assessment tasks:

Online multiple choice exam: 1 hour 20 minutes in length - 50% weighting within the unit

Online Statistics Assessments 1 to 5: 5 x 2 hours in length - 25% weighting within the unit

Critical assessment of literature: 25% weighting within the unit

Statistics practical exercises (compulsory): 5 x 3 hours in length - ( - 5%* )

Project review assignment (compulsory): 1 week in length - ( - 5%* )

(*5% will be subtracted from the final unit mark for each incomplete exercise or assignment)

The overall pass mark for BIOL65161 is 65%. Should you fail to achieve this mark, you will be asked to (re-)submit any missing or failed elements and will have to achieve a mark of at least 65% in the referral exam (online multiple choice format).

On-the-spot online feedback will be provided on 5 weekly statistics assessed assignments and a formative test. Students are also provided with oral feedback and individual help in understanding course content and in applying what is learnt to the students’ own projects during practicals and discussion groups.

   The following book is compulsory and is provided to all students on the course:

   Crawley, M.J, Statistics: An introduction using R. 2nd edition. (Wiley, 2015).