Level: 100 level. Read more information on levels in our FAQs

Fees:  Please see Fees and payments

Lectures: 36 hours 

Classes: 18 hours

Assessment*: Two written examinations

Typical credit**: 3-4 credits (US) 7.5 ECTS points (EU)

*Assessment is optional

**You will need to check with your home institution

For more information on exams and credit, read Teaching and assessment

No previous knowledge of statistics will be assumed, but the use of formulae and the ability to perform basic algebraic manipulations will be necessary. Some knowledge of basic calculus, although not necessary, would be an advantage.

• Data summaries
• Linear regression
• Experiments
• Probability
• Distribution theory
• Sampling
• Point estimation
• Hypothesis testing

• To understand that the point of statistics is to answer questions about the world.
• To learn to work with data, from constructing simple visual and numerical summaries, to fitting models and assessing the accuracy of their predictions.
• To develop the ability to critically evaluate uses (and misuses) of statistics.

Department of Statistics at LSE has a distinguished history. Its roots can be traced back to the appointment of Sir Arthur Lyon Bowley, an alumnus of the University of Cambridge, at LSE in 1895. He was appointed Chair in Statistics in 1919, probably the first appointment of its kind in Britain. The Department of Statistics was submitted jointly to REF 2014 with LSE's Department of Mathematics: 84% of the research outputs of the two departments were classed as either world-leading or internationally excellent in terms of originality, significance and rigour.

The department has an international reputation for development of statistical methodology that has grown from its long history of active contributions to research and teaching in statistics for the social sciences.

On this three week intensive programme, you will engage with and learn from full-time lecturers from the LSE’s statistics faculty.

There will be no need to rely on a particular textbook, as full notes will be provided. There are several good textbooks at the right level for this course, such as:

P. Newbold, Statistics for Business and Economics (6th edition or later), Prentice Hall (2007-). 

R.J. Larsen and M.L. Marx, An Introduction to Mathematical Statistics and Its Applications (3rd edition or later), Prentice Hall (2001-).

*A more detailed reading list will be supplied prior to the start of the programme

**Course content, faculty and dates may be subject to change without prior notice