Postgraduate Course: Statistics and Data Analysis (PGBI11003)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This is an introductory statistics course for quantitative geneticists and bioinformaticians. The syllabus covers basic R skills, probability and distribution theory, hypothesis testing, non-parametric methods, analysis of variance, linear regression, and generalised linear models with random effects. Teaching is through a combination of lectures, exercises, and computer-based practicals, using the R programming language for statistical computing. Students will be required to complete two assessed in-class assignments, one assessed quiz, and one open book exam. |
| Course description |
Not entered
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2023/24, Available to all students (SV1)
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Quota: 73 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 41,
Supervised Practical/Workshop/Studio Hours 16,
Revision Session Hours 6,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
133 )
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| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
1 x Assessed Quiz (10%)
2 x In Course Assignments (Total 40%)
1 x 2-hour examination (50%)
|
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Students who successfully complete the course will have a solid grounding in statistical methodologies required for quantitative biology.
- Students who successfully complete the course will have the requisite knowledge and experience to identify appropriate statistical approaches for analysing different types of genetic and bioinformatic data.
- Students who successfully complete the course will be able to apply statistical methodologies correctly and interpret results carefully.
- Students who successfully complete the course will be experienced in the use of the R programming language for statistical computing.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | QGGA Stats&DA |
Contacts
| Course organiser | Dr Cei Abreu-Goodger
Tel:
Email: |
Course secretary | Miss Zofia Bekas
Tel: (0131 6)50 5513
Email: |
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