Postgraduate Course: Further Statistics (PUHR11051)
Course Outline
| School | Deanery of Molecular, Genetic and Population Health Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course is designed to consolidate understanding of the key statistical concepts introduced in the core Introduction to Statistics (ItS) course, and build on these, extending knowledge and skills to:
1) Further types of simple analysis, and more advanced methods (eg for more than 2 groups, using data transformations, repeated measurements).
2) Use of stratification to explore confounding and effect modification.
3) Sample size calculations. |
| Course description |
Not entered
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2019/20, Available to all students (SV1)
|
Quota: 45 |
| Course Start |
Semester 2 |
| Course Start Date |
13/01/2020 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 20,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
|
| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Exam (100%) |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | Further Statistics | 2:00 | |
Learning Outcomes
| By the end of the course students will be able to: ¿ Select and apply a data transformation/method of analysis appropriate to each of a variety of analytical objectives and data distributions/structures ¿ Use both a calculator and the software package SPSS to perform a broad range of statistical analyses, and be able to interpret these appropriately ¿ Understand the issues in sample size estimation and undertake simple sample size calculations ¿ Understand the rationale for stratification and deploy this technique to explore confounding and effect modification ¿ Interpret appropriately the results of statistical analyses undertaken New topics to be covered (additional to ItS): ¿ Sample size estimation for simple studies ¿ Analysis of variance (including for repeated measures data) ¿ Non-parametric/ distribution-free methods, including non-par correlation ¿ Confidence limits for median and difference of two medians ¿ Assessment of measurement quality/agreement between a pair of variables by the methods of McNemar, kappa and Bland-Altman. ¿ Chi-squared test for association in larger two-way tables, including trend test and paired proportion data ¿ Stratification, including brief introduction to: Mantel-H adjusted OR for association in 2x2 tables stratified by a third variable (and chi-squared test) ¿ Introduction (only) to logistic regression as alternative for trend test and MH adjusted OR
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Contacts
| Course organiser | Dr Pam Warner
Tel: (0131 6)50 3248
Email: Pam.Warner@ed.ac.uk |
Course secretary | |
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