This course further develops key concepts in the statistical sciences including hypothesis testing, linear modelling and the analysis of data using statistical software.

On-campus Lectures: 20 x 1 hour lectures

On-campus Labs: 10 x 1.5 hour labs (several times available)

Drop-in help rooms: 20 x 1 hour optional sessions

Statistics 2R: Probability 1

Statistics 2S: Statistical Methods, Models and Computing 1

Mathematics 2A

Mathematics 2B

Statistics 2X: Probability 2

End-of-course examination (75%); coursework (25%).

Details about assessments will be included in the course handbook.

The aims of this course are:

■ to introduce students to key formal concepts used in statistics such as hypothesis testing and statistical modelling

■ to further equip students to apply statistical methods and models to solve problems from a wide range of disciplines and real life scenarios

■ to develop the ability of students to communicate results of statistical analysis in clear, non-technical language

■ to further develop students' statistical analysis software skills

■ to promote an interest in statistical science and data analysis and encourage students to study more advanced courses.

By the end of this course students will be able to:

■ formulate hypothesis tests using terms such as null and alternative hypotheses and carry out a range of common hypothesis tests

■ formulate linear models in algebraic and vector-matrix notations, derive estimators for model parameters and interpret model parameters

■ build linear models, assess the assumptions and suitability of fitted linear models and select between different models

■ generate, interpret and communicate the output of statistical software related to methods covered in the course