• Home
• Study
• Study Information
• Modules
• Module Information

Quantitative Research with Microsoft Excel

Module description

‘Violent crime is up by 10%!’ ‘Opinion polls suggest Tory landslide!’ ‘Barbeques cause cancer!’ These are just some of the types of quantitative research that we see in the media. But how do we know that these statistics are sound? Could the design of the studies be flawed? And, as a student, how do you go about designing robust surveys or experiments yourself and analysing the results? This module introduces you to the key concepts in quantitative design and data collection. It then builds on these to show you how to analyse this data confidently using Microsoft Excel.

Employers value highly skills such as how to collect, interpret and present quantitative data. This module is therefore suitable for all social science students. Absolutely no prior knowledge of statistics is needed.

Module aims - intentions of the module

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)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. 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;

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 4. 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;

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 6. Demonstrate an ability to present quantitative data effectively and clearly; and
• 7. Demonstrate enhanced numeracy skills which will be desirable to employers.

Syllabus plan

Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following themes:

• Research questions, variables and hypotheses.
• Populations and samples.
• Experiments in the social sciences.
• Survey research and polls.
• Descriptive statistics.
• Data visualisation and graphs.
• Correlation.

Lectures will be complemented by practical sessions which will focus on teaching hands-on skills including data entry and basic analysis using Microsoft Excel.

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Indicative learning resources - Basic reading

Bryman, A. (2012). Social Research Methods (4th edition). Oxford: Oxford University Press.

Groves, R.M. et al. (2009). Survey Methodology. Hoboken: Wiley.

De Vaus, D. (2001). Research Design in Social Research, London, New Delhi, Thousand Oaks CA: SAGE publications, 3rd Edn.

Spiegelhalter, D. (2020) The Art of Statistics Pelican Books: Milton Keynes

Indicative learning resources - Web based and electronic resources

Electronic Library http://as.exeter.ac.uk/library/resources/e-resources/elibrary/ and select the following resource subject: General or resource type: Reference resources (Sage Research Methods Online)

Key words search

Social science, surveys, quantitative, research design, statistics, data analysis, Excel