MT5762 Introductory Data Analysis

Academic year

2024 to 2025 Semester 1

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Not available to Undergraduate students.

Planned timetable

Monday, Thursday, Friday 3:30pm-5pm and Tuesday 4pm-5:30pm

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr M L Burt

Dr M L Burt
This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr Fergus Chadwick

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

This module provides coverage of essential statistical concepts and analysis methods relevant to commercial analysis. Specifically: the different types of data and their numerical/graphical treatment; basic probability theory and concepts of inference; fundamental statistical concepts with particular emphasis on sampling issues; basic statistical models and tests; linear models; introductory computer-intensive inference. This module is a short intensive course and is a core, preliminary, requirement for the MSc in Applied Statistics and Datamining. It covers material essential for study of the more advanced statistical methods encountered in subsequent modules.

Relationship to other modules

Pre-requisites

STUDENTS MUST HAVE GAINED ADMISSION ONTO AN MSC PROGRAMME

Anti-requisites

YOU CANNOT TAKE THIS MODULE IF YOU TAKE MT5756

Assessment pattern

Coursework = 100%

Re-assessment

Coursework = 100%

Learning and teaching methods and delivery

Weekly contact

Four 1.5-hour lectures (x 5 weeks), 1 tutorial (x 5 weeks)

Scheduled learning hours

35

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

115

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Understanding of fundamental applied statistical tests and models, ranging from simple univariate tests to linear models
  • Understanding of the basics of survey and experimental design and associated sampling strategies and biases
  • The fitting and interpretation of simple models with R as the exemplar language
  • Summarising and presentation of data, along with reporting of the results of statistical models to lay and technical audiences