Module Provider: |
Applied Statistics |
Number of credits: |
10 [5 ECTS credits] |
Level: |
I (Intermediate) |
Terms in which taught: |
Autumn |
Module Convenor: |
Dr
KL
Ayres |
Pre-requisites: |
GCSE Mathematics |
Co-requisites: |
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Modules excluded: |
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Module version for: |
2006/7 |
Aims:
This module provides an introduction to statistical methods relevant to students of Pharmacy. The objective is to introduce students to key issues in the design of research studies in the medical and pharmaceutical sector; and to expose them to a range of relevant, but quite specific, techniques for analysis and interpretation of data. |
Assessable learning outcomes:
On completion of this module students will be able to:
apply techniques to summarise and present data effectively,
apply basic techniques to analyse data and interpret the results,
identify the important concepts of research design, hypothesis generation and the setting up of a "fair trial",
describe the aetiology of disease, and identify and make distinctions between association and causation,
explain important aspects of epidemiology and population effects, and clinical trials. |
Additional outcomes:
Students will be introduced to the idea of effective team working in a multidisciplinary environment, together with the importance of working effectively with a professional statistician. This module is not intended to create statisticians, but scientists who are statistically aware.
Students will be introduced to Excel as a vehicle for data management and presentation and a statistical package such as Stata, epi-info or Minitab. |
Outline content:
Data and its description using tabular and graphical methods
Statistical computing using relevant software packages
Analysis of data - means, variances, confidence intervals, hypothesis tests
Correlation and causation - how to measure and interpret these effects
Key issues in study design - objective setting, research hypotheses, trial design
Epidemiology - case-control and cohort studies and their analysis
Clinical trials - trial design and analysis, randomisation, protocols, sample size. |
Brief description of teaching
and learning methods:
Lectures, supported by tutorials and practicals. |
Contact hours:
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Autumn |
Spring |
Summer |
| Lectures |
20 |
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| Tutorials/seminars |
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| Practicals |
10 |
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| Other contact (eg study visits) |
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| Total hours |
30 |
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| Number of essays or assignments |
2 |
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| Other (eg major seminar paper) |
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Assessment:
Coursework:
Two assignments which will include analysis and presentation of data
Relative percentage of coursework : 40%
Penalties for late submission:
In accordance with Faculty policy 10% of marks will be deducted from practical work which is submitted up to one week late. Work submitted later than this will receive no credit unless there are extenuating circumstances.
Examinations:
One paper of 2 hours duration 60%
Requirements for a pass:
An overall mark of at least 40%
Reassessment arrangements:
One examination paper of 3 hours duration |
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