Dr Anastasia Kakou

The course is designed for students without a strong background in Mathematics, e.g. without A level Mathematics, and is suitable for students who wish to learn basic statistical methods for analysing social science data. This course cannot be taken with ST102 Elementary Statistical Theory (nor its respective half-units ST109 and ST110) or ST107 Quantitative Methods (Statistics).

A grade B in GCSE Mathematics or equivalent. No background in statistics is required.

A basic foundation in elementary statistical methods, theory and statistical reasoning. Basic use of computers to analyse data. Probability, random variable theory and distributions. Normal distribution, sampling concepts and sampling distributions. Estimation, significance tests and confidence intervals, one and two-sample methods. Test for proportions, simple contingency tables. Linear regression, correlation. Basic decision theory.

This course will be delivered through a combination of classes and lectures totalling a minimum of 60 hours across Michaelmas Term and Lent Term. This year, some or all of this teaching may be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos. This course includes a reading week in Week 6 in each term.

Students will have a two hour Excel computer workshop in Michaelmas and Lent terms. Summer term session will primarily be devoted to revision. 

Exercises will be set most weeks. The questions will count as continuous assessment. 

Notes will be provided and form the basic reading material. Pointers will be given to further reading.

Exam (80%, duration: 3 hours) in the summer exam period.
Continuous assessment (20%) in the MT and LT.

At least a pass mark is required for both assessment components (i.e., the summer term exam and the continuous assessment).

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.