|Delivery length / details
|1 x 2 Hour Miscellaneous
|16 x 1 Hour Lectures
|Assessment length / details
|On-line statistics exercise 1.
|On-line statistics exercise 2.
|On-line statistics exercise 3.
|On-line statistics exercise 4.
|On-line statistics exercise 5.
|3 Hours On-line statistics exam.
|On-line reading exercise.
|Literature review. Group wiki.
|Literature review. Individual.
|Research proposal. Group wiki.
|Research proposal. individual.
|Students must take elements of assessment equivalent to those that led to failure of the module.
|3 Hours On-line statistics exam. Students must take elements of assessment equivalent to those that led to failure of the module.
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
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.
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
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
Questionnaire technique and structure
Interviewing techniques, focus groups
Content analysis (textual, discourse, conversation, visual)
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
Identification of resources
These issues will be developed through a number of formative exercises delivered via e-learning. The final summative assessment will require students to produce, in consultation with individual members of academic staff, a comprehensive research plan in an unique area relevant to their scheme of study. If successfully completed, this plan will form the basis of the student'r final year dissertation when progressing to the final year of the BSc.
This module is at CQFW Level 5