Fundamentals of Quantitative Analysis
| Code | School | Level | Credits | Semesters |
| EDUC4313 | Education | 4 | 20 | Autumn UK |
- Code
- EDUC4313
- School
- Education
- Level
- 4
- Credits
- 20
- Semesters
- Autumn UK
Summary
The objective of this module is to further student's familiarity with the practice of quantitative data analysis in the social sciences at a foundation level. The lecture component of the module will explore a variety of the most commonly used statistical methods. The laboratory component, will provide students with an opportunity to apply these statistical techniques to the analysis of contemporary data. The module should provide a sound grasp of the possibilities, methods, and pitfalls inherent in quantitative social/health science research.
Target Students
Available to MA SocSci Research or PhD students within the DTP.
Classes
This module is delivered through a series of lectures.
Assessment
- 100% Exam (2-hour): Exam
Assessed by end of autumn semester
Educational Aims
The module aims to give students: (a) an understanding of fundamental statistical methods using contemporary topics and datasets, (b) a familiarity with appropriate statistical software and data management, (c) an understanding of Open Science principles and practices to enhance reproducibility of research.Learning Outcomes
1. Intellectual skills
On completion of the module, the student will be able to:
determine the appropriate techniques to be used for different types of data.
demonstrate the critical understanding necessary to produce and interpret research in social/health science using foundation level quantitative statistical analyses.
critically evaluate experimental research approaches, distinguishing between experimental and observational data.
2. Professional / practical skills
On completion of the module, the student will be able to:
conceptualise testable hypotheses and empirically test using foundation level statistical analysis.
critically interpret such analysis accurately.
3. Transferable / key skills
On completion of the module, the student will be able to:
produce, analyse and evaluate research and other reports based on the use and presentation of data.
input data, apply fundamental statistical analysis and interpret outputs.
understanding Open Science principles and practices to enhance reproducibility of research.