Download Proposed Introductory Statistics Course

SCHOOL OF ENGINEERING
COURSE PROPOSAL FORM
Course Name*:
Statistics for Biomedical Sciences
Course Proposer*:
Niall Anderson
Have you confirmed that the appropriate resources are in
place (finance, teaching staff, IT)*:
Yes
Have you confirmed that the appropriate support
services are in place (library, computing services)*:
Yes
Normal Year Taken*:
Postgraduate
Course Level*:
PG
Available to Visiting
Students?*
Available to All Students
Display in Visiting
Student Prospectus:
Yes
SCQF Credits*:
10
Credit Level*1:
11
Home Subject Area*:
Postgrad (School of Engineering)
Other Subject Area:
Course Organiser*:
Niall Anderson
Course Secretary:
?
% not taught by this
institution:
0%
Collaboration
Information:
Course organiser from School of Clinical Sciences &
Community Health, CMVM, University of Edinburgh
Total Contact
Teaching Hours*:
20
Any costs to be met
by students:
None
Pre-requisites
(course name &
None
code)*:
Co-requisites (course
name & code)*:
None
Prohibited
None
Combinations (course
name & code)*:
Visiting Students
Pre-requisites:
None
Short Description*:
The course provides an introduction to key concepts and
topics in the statistical methods typically used in
biomedical sciences, with particular attention to the
principles of good experimental design and appropriate
methods of analysis. It will also provide some training in
practical data analysis using specialist statistical
software.
Keywords2:
Statistics,
clinical
trials,
experimental
design,
randomisation, ANOVA, reproducibility, diagnostic tests,
regression
Fee Code if invoiced
at Course level:
Not applicable
Default Course Mode
of Study*:
Classes & Assessment, excl. centrally arranged exam
Default Delivery
Period*:
Semester 1
Course Type*:
Standard
Summary of Intended Students should be familiar with the basic principles
Learning Outcomes*: underlying statistical thinking, including topics such as
types of data, the relationship of population to sample,
sampling methods, confidence intervals, hypothesis
testing and experimental design and randomisation.
They should understand and be able to apply simple one
and two-group parametric tests, correlation coefficients,
simple linear regression models, and simple fixed-effect
analysis of variance models. They should be able to
analyse correctly method comparison and reproducibility
studies and use the appropriate quantities to measure
performance of diagnostic and prognostic tests. They
should develop competence in implementing the above
methods in statistical software.
Special
Arrangements:
None
Components of
Assessment (inc. %
weightings)*:
Project = 100%
Exam Information*
(please remove 2nd
Sit if not applicable):
None
Syllabus/Lecture List:
1. Introduction to principles of statistical inference,
types of data and graphical and simple summary
measures
2. Basic probability and probability distributions
3. Confidence intervals – principles and simple 1 & 2
group continuous and categorical examples
4. Hypothesis testing –
examples as session 3.
principles
and
same
5. Correlation and simple linear regression
6. Study design principles – randomisation and
blocking
7. Study design principles – clinical trials and power
issues
8. One and Two-way analysis of variance models
9. Method comparison and reproducibility methods
10. Diagnostic testing – sensitivity, specificity, PPV,
NPV and ROC curves
Study Pattern/Course 10 x 1 hour lectures; 5 x 2 hour practical sessions
Structure:
Benchmark
Statements Assessed:
Teaching Load*
(select from attached
list):
Reading Lists:
10 x 1 hour lectures; 5 x 2 hour practical sessions
1. Statistics at Square One, Ninth Edition (1997).
Swinscow,
TDJ.
BMJ
(Download
at
http://www.bmj.com/statsbk/)
2. Medical Statistics at a Glance (2000). Petrie, A
and Sabin, C. Blackwell.
3. Practical Statistics for Medical Research (1991)
Altman, D.G. Chapman and Hall/ CRC.
Convenor of Board of
Examiners:
?
Footnotes:
*
Indicates mandatory fields.
1.
Normally:
Undergraduate Courses:
Years 1 and 2 = Level 8
Year 3
= Level 9
Year 4
= Level 10
Year 5
= Level 11.
MSc Courses
2.
= Level 11.
Keywords are used to help staff/students find a course when searching
the DRPS (Degree Regulations and Programme of Study).