MAS360 Practical and Applied Statistics

Both semesters, 2017/18 20 Credits
Lecturer: Dr Eleanor Stillman uses MOLE Timetable
Aims Outcomes Teaching Methods Assessment Full Syllabus

This course aims to give you practice in solving problems of the sort you will encounter in real life as a professional mathematician or statistician. It gives training and practice in the various stages: problem definition, preliminary examination of data, modelling, analysis, computation, interpretation and communication of results. It is comprised of a series of exercises (not assessed) and projects (assessed).

Teaching is directed towards skills development. Specific guidance is given regarding presentation skills (oral and written) and group working, but no new technical material is taught. Instead, you are encouraged to recall and collate the technical material gained over the entire remainder of your degree programme and to identify and implement those methods which are appropriate and useful in addressing the problem at hand. This vital skill, of synthesizing and evaluating your existing knowledge, allows you to show yourself at your best in examinations, interviews and the early days of a future career.

Prerequisites: MAS223 (Statistical Inference and Modelling)
Not with: MAS301 (Group Project)
No other modules have this module as a prerequisite.


Outline syllabus

There is no technical syllabus for this course; indeed it is deliberately arranged that no new theory is needed, although students may need to use extended versions of familiar topics or invent ad hoc methods. Instruction is given in writing reports and in tackling imprecisely worded or open-ended problems. Feedback on projects attempted continues this instruction.

Office hours

Please contact lecturers by email for appointments.



Aims

  • To develop students' skills in open-ended tasks with a substantial statistical aspect.
  • To develop students' abilities to report on the results of their investigations.

Learning outcomes

  • conduct investigations based on data in which either the data are untidy or the investigations needed are ill-defined
  • apply statistical knowledge and awareness in practical situations
  • take responsibility for defining tasks more precisely
  • prepare project reports of a high standard
  • engage in effective oral presentation
  • work effectively in a group

Teaching methods

Lectures, discussions, consultation sessions, Mole discussion boards and feedback. It is misleading to designate the sessions as `lectures' since activities in them will be variable and will often not be well described as lectures.


30 lectures, no tutorials

Assessment

Entirely continuous assessment, through project reports and presentations. The weighting and deadlines will be announced during the module.

Full syllabus

There is no technical syllabus for this course.

Timetable (semester 1)

Tue 13:00 - 13:50 lecture   Hicks Lecture Theatre A
Fri 09:00 - 09:50 lecture   Hicks Lecture Theatre A