Statistics 3B: Biostatistics STATS3012

  • Academic Session: 2024-25
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 3 (SCQF level 9)
  • Typically Offered: Either Semester 1 or Semester 2
  • Available to Visiting Students: Yes
  • Collaborative Online International Learning: No

Short Description

This course provides an introduction to statistical methods and concepts relevant to problems in medicine, especially in clinical trials and epidemiological studies, and discusses the principal ethical issues that arise. It also covers survival analysis as a means of modelling measurements made over an interval of time.

Timetable

20 lectures

fortnightly tutorials

2 two-hour practical sessions

Requirements of Entry

The normal requirement is that students should have been admitted to the third year of the Designated Degree programme in Statistics.

Co-requisites

The courses prescribed in the Designated Degree programme to which the student has been admitted.

Assessment

90 minute, end of course examination (100%)

Main Assessment In: April/May

Course Aims

The aims of this course are:

■ To provide an appreciation of the application of statistical methods and concepts to problems in medicine, especially in clinical trials and epidemiological studies, and to discuss the principal ethical issues that arise; and

■ To introduce survival analysis as a means of modelling measurements made over an interval of time, such as the survival time of a patient (time from treatment to death).

Intended Learning Outcomes of Course

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

■ describe a range of biostatistical study designs, describe their key features, and, in simple cases, determine the appropriateness of each one for real epidemiological investigations.

■ describe a range of summary statistics and simple statistical models used to quantify biostatistical data, and be able to apply these to real data.

■ describe basic measures for quantifying the impact of a covariate factor on disease risk, and compute and interpret them in real epidemiological studies.

■ describe elementary features of survival data, the Kaplan Meier estimator and the proportional hazards model, and be able to apply them to real data.

■ calculate appropriate sample sizes for clinical trials and interpret them in the context of real clinical trials.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.