Student must be registered on MSci Forensic Science, MSci Forensic Investigation or MSci Policing and Criminal Investigation or MChem Chemistry

IT laboratories equipped with Excel, SPSS and R.

1. DEMONSTRATE A SYSTEMATIC UNDERSTANDING OF PROFESSIONAL LEVEL RESEARCH PLANNING SKILLS
Enquiry
Knowledge & Understanding
Learning
Reflection

2. DEMONSTRATE ADVANCED SKILLS IN DATA HANDLING USING STANDARD STATISITICAL SOFTWARE Analysis
Application
Communication
Knowledge & Understanding
Problem Solving

3. DEMONSTRATE HIGH-LEVEL SKILLS IN QUALITATIVE RESEARCH METHODS, USING CONTEMPORARY METHODS
Analysis
Application
Knowledge & Understanding
Problem Solving

Two course work assignments:

The first will take the form of a 1000 word analysis of qualitative data (weighted at 40%, testing learning outcome 3). The qualitative analysis will be based on a coded interview transcription and will draw on relevant literature to help substantiate the themes it identifies.

The second will be a portfolio of work, showcasing statistical analysis using a variety of software (weighted at 60%, testing learning outcomes 1 and 2). Students will be given pre-determined scenarios with associated raw data sets. The students will be required to carry out statistical analysis through at least two different platforms (for example, Excel, SPSS or RStudio), demonstrating their understanding of the software, how to manipulate and analyse data, whilst justifying their reasoning for each stage of analysis.

You will learn to critically engage with the literature at a deep level, and design experiments and studies that produce meaningful data of publishable quality. You will learn methods used to collect both quantitative and qualitative data. Your learning will be underpinned by tuition in the use of statistical analysis software such R to simulate, present, explore and test data at a professional level. Topics such as data management, advanced tests for difference, power analysis, and methods of data reduction and exploration will be covered. In the qualitative element of this module you will learn about observational studies, semi-structured interviews, discourse analysis, grounded theory, and how to use Nvivo to transcribe interviews. You will also hone your report writing skills. This module will be taught with specific reference to research in your subject area.

This module will build on the research methods learning that you have gained in previous modules. Its content will be taught through mixture of a Virtual Learning Environment, 34 hours of workshop attendance and three, one hour classes with your personal tutor during which you will gain formative feedback on your research ideas.

Barbour, R. (2014) Introducing Qualitative Research. 2nd ed. London: Sage Publications.

Lander, J. P. (2014) R for Everyone: Advanced Analytics and Graphics. Boston (MA): Addison-Wesley.

Olsen, W. (2012) Data Collection: Key Debates and Methods in Social Research. London: Sage Publications.

Silverman, D. (2017) Doing Qualitative Research. 5th ed. London: Sage.

Stinerock, R. (2018) Statistics with R. A beginners guide. London: Sage.

This module will build on the research methods learning that you have gained in previous modules. Its content will be taught through mixture of a Virtual Learning Environment, 28 hours of workshop attendance and three, one hour classes with your personal tutor during which you will gain formative feedback on your research ideas.

You will learn to critically engage with the literature at a deep level, and design experiments and studies that produce meaningful data of publishable quality. You will learn methods used to collect both quantitative and qualitative data. Your learning will be underpinned by tuition in the use of statistical analysis software such as R and Nivo to simulate, present, explore and test data at a professional level.