Gwybodaeth Modiwlau
Course Delivery
| Delivery Type | Delivery length / details |
|---|---|
| Lecture | 10 Hours. |
| Seminars / Tutorials | 10 Hours. |
| Practical | 10 Hours. |
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | Report-type assignment (= 2,5000/3,000 word essay) | 50% |
| Semester Assessment | Report-type assignment (=2,500/3000 word essay) | 50% |
| Supplementary Assessment | Re-submission of failed coursework |
Learning Outcomes
On successful completion of this module students should be able to:
* Summarise categorical and quantitative data, explain averaging, variance and standard deviation
* Explain probability distributions and identify when binomial and normal distributions may be applied.
* Discuss various sampling methods, and when they should be applied.
* Estimate confidence intervals, significance levels, and demonstrate hypothesis testing (parametric and non-parametric).
* Demonstrate principles of Bayesian inference, and apply techniques such as decision trees.
* Apply some simulation techniques for forecasting
* Discuss how different methods of presenting risk can affect attitudes towards towards decision making.
* Describe different research designs and evaluation methods and how, and when these should be applied to different problem situations.
* Critically appraise a research article in the information systems field.
Brief description
The module should provide students with a `toolbox? of numerical and statistical techniques to enable them to use such methods for data analysis and presentation. The module is also intended to provide students with the skills to critically appraise research articles that have a strong quantitative component. There will be an emphasis on the problems of risk communication in the module as well.
Content
The following topics will be covered:Probability and probability distributions, Samples and populations, Summarising data (measures of variation), Confidence intervals, Hypothesis testing (parametric and non-parametric), Association of categorical variables, Use of SPSS, Experimental design, Evaluation designs, Critical appraisal of research articles, Presentation and interpretation of statistical/numerical data, Risk communication.
Module Skills
| Skills Type | Skills details |
|---|---|
| Application of Number | Integral to the module ¿ statistical methods, data analysis and presentation of numerical information |
| Communication | Emphasis on the problems of presenting numerical/statistical information in a meaningful way for different audience |
| Improving own Learning and Performance | Problem-based learning approach should foster development of positive attitudes towards lifelong learning |
| Information Technology | Use of statistical software packages such as SPSS |
| Personal Development and Career planning | Case study problems should enhance students¿ understanding of workplace problems |
| Problem solving | Critical appraisal exercises and reflection on problems set to encourage student-centred learning |
| Research skills | Integral to the module - data analysis and presentation skills, statistical methods |
| Subject Specific Skills | Skills specific to quantitative analysis |
| Team work | Students will be encouraged to work in small groups on a problem |
Notes
This module is at CQFW Level 6