Applied Statistics
Entry requirements
A second-class honours degree (2:2) or above, with mathematics or statistics as a main subject.
Other degrees or professional qualifications may also be acceptable, such as the Birkbeck Graduate Certificate in Statistics for Data Science or the Graduate Diploma of the Royal Statistical Society.
Applications are reviewed on their individual merits and your professional qualifications and/or relevant work experience will be taken into consideration positively. We actively support and encourage applications from mature learners.
Months of entry
October
Course content
This applied statistics course is ideal if you are considering a career move into statistics, or if your work already involves aspects of data collection and exploration, interpretation of statistics, or modelling and forecasting time-dependent phenomena. It delivers a strong theoretical background but is also practically oriented to develop your ability to tackle new and non-standard problems with confidence.
Why choose this course?
- This course offers you a comprehensive curriculum covering frequentist and Bayesian methods, statistical machine learning and advanced computational techniques.
- It has a favourable staff-student ratio to ensure high-quality teaching and support, with time for one-on-one consultation as needed.
- It is accredited by the Royal Statistical Society (RSS), so that our graduates may be eligible to attain Graduate Statistician (GradStat) status.
- It benefits from being led by experienced statisticians and mathematicians with active research interests in theoretical and applied statistics.
What you will learn
We emphasise the mutual dependence of practice and theory throughout the course, with a focus on hands-on application through real-world datasets to equip you with the skills to analyse and interpret complex data and communicate findings effectively.
You will learn to formulate real-world problems as statistical models and implement them using statistical software. You will also gain a solid grounding in core statistical methodologies, including:
- regression
- ANOVA
- generalised linear models along with an introduction to Bayesian modelling
- a wide variety of advanced computational statistics and machine learning methods.
How you will learn
Teaching on this course is through a combination of lectures (pre-recorded), seminars and practical computing sessions. In lectures an overview of the topic engages you with the material through theory worked problems and example applications. Seminars are focused around discussion and problem-solving while computing sessions allow you to gain practical experience in the analysis and modelling of data.
This course is available to study full- or part-time. It has an evening timetable with classes taking place in the evening, so that you can fit your studies in around other work or family commitments. You will also be supported by comprehensive resources, including a dedicated subject librarian and high-quality recordings of lectures.
We offer this course as a Master’s and a Postgraduate Certificate. For the Certificate, you study fewer modules and do not complete a dissertation.
- We bring together research and teaching across computer science, mathematics and statistics which creates significant interdisciplinary synergies.
- We have active research groups in Algorithms, Data Science and Artificial Intelligence, Logical Methods, and two research centres: Birkbeck Institute for Data Analytics and Birkbeck Knowledge Lab, that host visiting speakers and organise seminars you can attend.
- You will have access to a wide range of study resources, including University of London seminar programmes in probability and statistics, and excellent library facilities close by in Bloomsbury. Extensive computing facilities include PCs and UNIX platforms.
- You will be studying alongside a diverse group of passionate and enthusiastic students from various backgrounds, careers and cultures, including professionals in data science, finance, economics and computer science.
Careers and employability
On successfully graduating from this MSc Applied Data Science, you will have gained an array of important transferable skills, including the ability to:
- understand and apply computationally intensive statistical methodology
- abstract the essentials of a practical problem and formulate an appropriate statistical or mathematical model
- solve problems using an analytical and systematic approach
- understand advanced, abstract material
- learn independently by study of a range of sources including learned journals
- develop self-motivation, time management and organisation.
Studying this course will prepare you for a career path in roles in a range of professions including:
- actuary
- data analyst
- data scientist
- economist
- financial manager
- financial risk analyst
- machine learning engineer
- operational researcher
- research scientist
- statistician.
Graduates from this course have gone on to be employed at various organisations including G-Research, CodeMagus, The Centre for Policy Studies and Imperial College London.
We offer a comprehensive careers service - Careers and Enterprise - your career partner during your time at Birkbeck and beyond. At every stage of your career journey, we empower you to take ownership of your future, helping you to make the connection between your experience, education and future ambitions.
Information for international students
If English is not your first language or you have not previously studied in English, our usual requirement is the equivalent of an International English Language Testing System (IELTS Academic Test) score of 6.5, with not less than 6.0 in each of the sub-tests.
If you don't meet the minimum IELTS requirement, we offer pre-sessional English courses and foundation programmes to help you improve your English language skills and get your place at Birkbeck.
Qualification, course duration and attendance options
- MSc
- part time24 months
- Campus-based learningis available for this qualification
- full time12 months
- Campus-based learningis available for this qualification
- PGCert
- part time12 months
- Campus-based learningis available for this qualification
Course contact details
- Name
- Student Advice Service
- studentadvice@bbk.ac.uk
- Phone
- +44 (0)20 3907 0700