Gwybodaeth Modiwlau
Course Delivery
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | Assignment 2500 Words | 50% |
| Semester Exam | 2 Hours On-line exam 40 questions | 50% |
| Supplementary Assessment | Assignment 2500 Words | 50% |
| Supplementary Exam | 2 Hours On-line exam 40 questions | 50% |
Learning Outcomes
On successful completion of this module students should be able to:
1. Understand how to design a quantitative research project and the critical issues which this requires
2. Understand and be able to apply the basic principles of statistics and statistical terminology
3. Use Excel to process and display simple statistical data
4. Analyse statistical data using SPSS, selecting the appropriate tests and interpreting them correctly with underlying assumptions applied
5. Display statistical information appropriately and accurately (graphs and charts)
6. Critically interpret visual statistical information (graphs and charts)
7. Use SPSS effectively in the demonstration of 3 and 4 above
8. Have a critical understanding of some of the controversies within statistical analysis and their presentation
Brief description
This module specifically addresses the statistical analysis of quantitative research data, necessary because a positivist research paradigm is common in this field of study, and this content is a required component for our BSc programme. It will enable students to understand the basics of statistics, and to use both Excel and SPSS in their analysis, using both descriptive and inferential statistics.
Content
Quantitative design basics
Different types of data
Measures of central tendency and percentages
Normality testing
Statistical significance
Inferential statistics, including measuring difference and measuring correlation
Displaying statistical data
Interpreting statistical data (including errors in interpretation and presentation)
Use of Excel
Use of SPSS
Module Skills
| Skills Type | Skills details |
|---|---|
| Adaptability and resilience | Students will need to be able to work independently to a certain degree, as described above, trying initially to work their own way through problems. Statistics is quite a different type of study from that with which they may be familiar, and is very different from any other module on these schemes, so they will need to be able to cope with a different way of learning. |
| Co-ordinating with others | Lectures will be interactive, with some scope for small group discussion in places. Practicals will be largely individually completed, but experience has shown that students tend to offer each other help and assistance throughout, making it a much more communal experience. The small experiment will necessitate students working in pairs for part of it. |
| Creative Problem Solving | Students will need to navigate their way through a workbook in some of the practicals, utilizing a guidebook designed for the purpose, which will help them to learn how to think their way through problems and questions independently, but asking for help when they need it. They will also input into the design of a small in-class experiment, which will help them to see what questions need to be asked in constructing such a project. |
| Critical and analytical thinking | Students will need to be able to see the advantages and limitations of using quantitative methods, and inferential statistics, engaging with some of the critical debates on these issues, and demonstrating an ability to be critical in the assessments. |
| Digital capability | The practicals will all be conducted in computer rooms using Excel and SPSS, so a reasonably confident attitude towards computer software is needed. The assignments will both need to be completed using specific computer software. |
| Professional communication | The first assignment requires students to write to a high level of academic competency. |
| Real world sense | The whole module is deliberately embedded within real-world research, and will grapple with some of the real controversies regarding inferential statistics. It will also incorporate a small scale experiment which they will help to design, be participants, and analyse the findings, showing them how they can apply knowledge of statistics to real research questions. |
| Reflection | Students will be introduced to some areas of controversy, and so will need to be reflective in the way they develop these understandings in their own work. |
| Subject Specific Skills | Students’ knowledge of statistics and developing ability to use SPSS will make the prospect of using a quantitative design realistic, should they decide to undertake an empirically-based dissertation. |
Notes
This module is at CQFW Level 6