This course introduces students to key concepts in the statistical sciences including data visualisation, parameter estimation, statistical inference and analysis using statistical software.

On-campus Lectures: 15 x 1 hour lectures

On-campus Labs: 10 x 2 hour labs (several times available)

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

Statistics 2R: Probability 1

Mathematics 2A

Mathematics 2B

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 sampling distributions and point and interval estimation

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

■ to train students to communicate results of statistical analysis in clear, non-technical language

■ to introduce students to statistical analysis software

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

■ to introduce students to the science of collecting, organizing, summarizing, analyzing, and presenting data

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

■ recognise different types of data structures and summarize data using appropriate graphical and numerical methods

■ manipulate and analyse data with appropriate methods using statistical software

■ describe sampling methods and derive sampling distributions of statistics such as sample mean

■ define point and interval estimates and implement point and interval estimation techniques such as maximum likelihood estimation

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