Module Information
Course Delivery
| Delivery Type | Delivery length / details |
|---|---|
| Lecture | 17 x 1 Hour Lectures |
| Miscellaneous | 1 x 2 Hour Miscellaneous |
| Lecture | 16 x 1 Hour Lectures |
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | On-line statistics exercise 1. | 4% |
| Semester Assessment | On-line statistics exercise 2. | 4% |
| Semester Assessment | On-line statistics exercise 3. | 4% |
| Semester Assessment | On-line statistics exercise 4. | 4% |
| Semester Assessment | On-line statistics exercise 5. | 4% |
| Semester Exam | 3 Hours On-line statistics exam. | 30% |
| Semester Assessment | On-line reading exercise. | 5% |
| Semester Assessment | Literature review. Group wiki. | 5% |
| Semester Assessment | Literature review. Individual. | 15% |
| Semester Assessment | Research proposal. Group wiki. | 5% |
| Semester Assessment | Research proposal. Individual. | 20% |
| Supplementary Assessment | Students must take elements of assessment equivalent to those that led to failure of the module. | 70% |
| Supplementary Exam | 3 Hours Students must take elements of assessment equivalent to those that led to failure of the module. | 30% |
Learning Outcomes
On successful completion of this module students should be able to:
1. Search and review the scientific literature to identify valid research questions
2. Identify appropriate methods of analysis for different types of research
3. Design statistically valid experiments
4. Identify and mitigate against confounding factors in research design
5. Demonstrate an understanding of the ethical issues involved in research
6. Analyze data using a range of quantitative and qualitative techniques
7. Interpret the results of data analyses and apply statistical knowledge in the evaluation of research investigations
Brief description
The course will cover the principles and practice of a range of basic quantitative and qualitative procedures of data analysis, coupled with an understanding of good research design and planning. Delivery will rely heavily on student-centered e-learning, supported by computer workshops. Through e-learning, students will receive training in the use of statistical software packages, literature searching and research design. Use of subject-specific tutorial videos through Abercast will ensure that students receive explanatory examples directly relevant to their particular subject area. Formative assessment will be through the use of e-exercises in Blackboard using adaptive release, prior to the submission of a fully developed research plan and an exam to test statistical skills learnt.
Content
Following a core foundation in basic procedures of data analysis, students will have the opportunity to select a limited number of techniques relevant to specific schemes of study. The subject material will include:
The nature of variability
Populations, samples and sampling strategies
Types of data
Probability
Standard deviation
Normal distribution
Sampling from the normal distribution, standard error
Students t distribution, t tests
Analysis of variance
Multifactorial analyses, blocking
Correlation and regression
Chi-square analysis, contingency tables
Non-parametric tests
Questionnaire technique and structure
Research planning
Running concurrently with the training in data analysis will be lectures on the basics of experimental design and research planning. These will include:
Literature searching and interpretation
Strategies and approaches to reviewing literature
Identifying hypotheses and research questions
Sampling strategies and size
Identification and mitigation of confounding factors
Appropriate research design
Ethical issues in research design
Protocol development
Identification of resources
Module Skills
| Skills Type | Skills details |
|---|---|
| Application of Number | Most aspects of the module will require manipulation of data and application of statistics. |
| Communication | Students will be required to write a clear, concise and precise research plan. |
| Improving own Learning and Performance | Students need to review and monitor progress of formative and assessed coursework in order to improve overall performance. |
| Information Technology | Literature searching and use of internet search engines use of statistical packages to analyse data. |
| Personal Development and Career planning | |
| Problem solving | Determine the most appropriate research design and methods of analysis to use with different types of data. |
| Research skills | Identification of research questions, research design, analysis of data and interpretation of the results in the context of an academic investigation. |
| Subject Specific Skills | |
| Team work |
Notes
This module is at CQFW Level 5