The degree involves studying courses to the value of 12 units over three years, plus LSE100.
First year
In your first year, you will take four compulsory courses. In addition, you will also take LSE100.
(* denotes a half unit course)
Elementary Statistical Theory
This is a theoretical statistics course which is appropriate whether or not your A level Mathematics course included statistics. It forms the basis for later statistics options.
Mathematical Methods
This is an introductory-level "how to do it" course designed to prepare you for using mathematics seriously in the social sciences, or any other context.
Programming for Data Science*
Covers the principles of computer programming with a focus on data science applications.
Managing and Visualising Data*
Explains the fundamental principles for effective manipulation and visualisation of data.
Courses to the value of one unit
LSE100*
A half unit, running across Autumn and Winter Term in the first year, LSE100 is compulsory for all LSE undergraduate students. This innovative and interactive course is designed to build your capacity to tackle multidimensional problems as a social scientist through interdisciplinary, research-rich education.
Second year
In your second year you will take a mixture of core and optional courses.
Algorithms and Data Structures*
Introduces the fundamental principles of data structures and algorithms and their efficient implementation.
Databases*
Covers the basic concepts of database management systems, including relational and other types of database management systems.
Either
Mathematical Proof and Analysis*
Provides an introduction to the use of formal definitions and proofs in mathematics, and to basic results of elementary logic, set theory and analysis. Specific topics covered are as follows: Logic, sets and functions, relations, real numbers, infimum and supremum, sequences, limits and continuity.
AND
Further Mathematical Methods (Linear Algebra)*
Covers: Vector spaces and dimension. Linear transformations, kernel and image. Real inner products. Orthogonal matrices, and the transformations they represent. Complex matrices, diagonalisation, special types of matrix and their properties. Jordan normal form, with applications to the solutions of differential and difference equations. Singular values, and the singular values decomposition. Direct sums, orthogonal projections, least square approximations, Fourier series. Right and left inverses and generalized inverses.
Or
EITHER
Further Mathematical Methods
It is divided into two halves: calculus and linear algebra. The calculus half explores how integrals may be calculated or transformed by a variety of manipulations, and how they may be applied to the solution of differential equations.
OR
Real Analysis*
This is a course in real analysis for those who have already met the basic concepts of sequences and continuity on the real line. Here we generalize these concepts to Euclidean spaces and to more general metric and normed spaces.
AND
Further Mathematical Methods (Linear Algebra)*
See description above.
Either
Probability and Distribution Theory*
Covers the probability, distribution theory and statistical inference needed for third year courses in statistics and econometrics.
AND
Applied Regression*
Statistical data analysis in R covering the following topics: Simple and multiple linear regression, model diagnostics, detection of outliers, multicollinearity and introduction to GLMs.
AND an optional course to the value of one whole unit
Or
Probability, Distribution Theory and Inference
Develops your knowledge of probability and statistics beyond the first-year course. It will also provide the probability and statistics basis for all third-year courses.
AND
Applied Regression*
Statistical data analysis in R covering the following topics: Simple and multiple linear regression, model diagnostics, detection of outliers, multicollinearity and introduction to GLMs.
AND an optional course to the value of 0.5 units
Third year
In your third year you will take three compulsory courses, and will choose options to the value of two units.
Machine Learning*
Focuses on the core machine learning techniques in the context of high-dimensional or large datasets (i.e. big data).
Artificial Intelligence*
Introduces the basic principles of artificial intelligence systems.
Applied Statistics Project*
Involves a critical investigation and collation of statistical data on a topic of your own interest.
Courses to the value of one unit from the below options:
Regression and Generalised Linear Models*
Covers the most important parts of the theory and application of regression models and generalised linear models.
Time Series and Forecasting*
Introduces the statistical analysis of time series data and simple models, and showcases what time series analysis can be useful for.
Bayesian Inference*
Examines statistical decision theory, Bayesian inference, implementation and applications.
Financial Statistics*
Covers key statistical methods and data analytic techniques most relevant to finance.
Multilevel and Longitudinal Models*
Considers statistical methods for the analysis of data with a multilevel (clustered) structure with applications in social research.
Optional course to the value of 1.5 units
For the most up-to-date list of optional courses please visit the relevant School Calendar page.
Where regulations permit, you may also be able to take a language, literature or linguistics option as part of your degree. Information can be found on the Language Centre webpages.
You must note, however, that while care has been taken to ensure that this information is up-to-date and correct, a change of circumstances since publication may cause the School to change, suspend or withdraw a course or programme of study, or change the fees that apply to it. The School will always notify the affected parties as early as practicably possible and propose any viable and relevant alternative options. Note that the School will neither be liable for information that after publication becomes inaccurate or irrelevant, nor for changing, suspending or withdrawing a course or programme of study due to events outside of its control, which includes but is not limited to a lack of demand for a course or programme of study, industrial action, fire, flood or other environmental or physical damage to premises.
You must also note that places are limited on some courses and/or subject to specific entry requirements. The School cannot therefore guarantee you a place. Please note that changes to programmes and courses can sometimes occur after you have accepted your offer of a place. These changes are normally made in light of developments in the discipline or path-breaking research, or on the basis of student feedback. Changes can take the form of altered course content, teaching formats or assessment modes. Any such changes are intended to enhance the student learning experience. You should visit the School’s Calendar, or contact the relevant academic department, for information on the availability and/or content of courses and programmes of study. Certain substantive changes will be listed on the updated undergraduate course and programme information page.