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Undergraduate Module Descriptor

SPA3002: Quantitative Research with Microsoft Excel

This module descriptor refers to the 2021/2 academic year.

Module Aims

The aim of this module is to introduce you, as social science students, to quantitative research design, data collection and analysis, so that you are both able to assess the research of others (e.g. in the media, in research articles) and use quantitative skills in your own research projects. This module covers the basics of quantitative research design and the scientific method, explaining how measuring variables allows us to test theories and hypotheses. It guides you in how to collect and manage high quality data, for example, such as surveys or experiments. It looks at examples of common sources of bias or misreporting of quantitative results. It also offers a basic guide to analysis; covering when and how to use descriptive statistics (e.g. percentages). Practical sessions will give you the opportunity to develop hands-on competency in using computer software (Microsoft Excel) to analyse data.

Intended Learning Outcomes (ILOs)

This module's assessment will evaluate your achievement of the ILOs listed here – you will see reference to these ILO numbers in the details of the assessment for this module.

On successfully completing the programme you will be able to:
Module-Specific Skills1. Demonstrate a high level of understanding pertaining to quantitative research design, data collection and basic analytical techniques;
2. Demonstrate an understanding of, and confidence with, computer software (Microsoft Excel) for data analysis;
3. Demonstrate a strong understanding of what makes some quantitative research ‘good’ and some ‘bad’ in quality;
Discipline-Specific Skills4. Demonstrate a strong understanding of quantitative research design in the social sciences at an introductory level;
5. Create a research question and hypothesis, and demonstrate the ability to critically evaluate these;
Personal and Key Skills6. Demonstrate an ability to present quantitative data effectively and clearly; and
7. Demonstrate enhanced numeracy skills which will be desirable to employers.