Postgraduate Course: Neuroimaging: Statistics (NEME11010)
Course Outline
| School | Deanery of Clinical Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | The purpose of this course is to make sure that the student has a good grasp of the basics of statistics commonly used to evaluate datasets derived from imaging research, how to assess the accuracy of diagnostic tests, and to deal with evaluating imaging changes over time. This will include sensitivity, specificity, positive and negative predictive values, interobserver reliability (for continuous and categorical variables), and repeated measures analyses. There will also be a section on how to assess a diagnostic paper and on the design, conduct and analysis of systematic reviews of imaging studies. |
| Course description |
Not entered
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2024/25, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
| Course Start Date |
16/09/2024 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 20,
Online Activities 20,
Formative Assessment Hours 2,
Summative Assessment Hours 2,
Revision Session Hours 20,
Directed Learning and Independent Learning Hours
36 )
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| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Assessment will consist of continuous, in-course assessments and a final assessment. In-course assessment will be composed of a mixture of multiple choice-type questions, short essays, practical tasks, contributions to discussions and group learning activities - and will be delivered in time with individual modules making up the course. Final assessment will normally include a combination of multiple choice-type questions and short essays and it will take place at the end of the course period.
A number of bespoke technologies and the University's online assessment tool QuestionMark Perception will be used to deliver the more interactive and visually driven elements of assessment.
The principle of constructive alignment will underpin all assessments. This will ensure the assessment tasks are aligned with the specific course objectives.
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| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
The programme aims to contribute to improved understanding of the use of neuroimaging in research by users from a wide range of different disciplines, including understanding the principals of study design to avoid bias, practicalities and limitations of different imaging techniques, and image analysis processes. This will improve the design, quality and interpretation of neuroimaging as used in research and help advance knowledge faster.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Special Arrangements |
All courses will be delivered taught by distance learning. Registered students are provided with a user name and password that allows them to access a protected course web site. The website houses a number of interactive tutorials that allow students to work with information in a self-paced manner to test their understanding of important concepts and principles. Online delivery will be supported through online discussions with peers and tutors. The website provides a variety of educational material and supports a range of approaches by the students to the material provided.
Study guides with lecture notes are available, either to be read on screen or printed by the students for private use. Selected readings from relevant journals and textbooks are also provided.
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| Additional Class Delivery Information |
Course will be delivered by distance learning. Students will be expected to spend 15-20 hour a week studying, including accessing online materials and tests and participating in online discussions. |
| Keywords | Not entered |
Contacts
| Course organiser | Prof Andrew Farrall
Tel: (0131) 537 3910
Email: andrew.farrall@ed.ac.uk |
Course secretary | Dr Charilaos Alexakis
Tel: 0131 537 3125
Email: C.Alexakis@ed.ac.uk |
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