Course Details in 2018/19 Session

Module Title	LM Social Research Methods II
School	COS - College Hub
Department	COS - College Hub
Module Code	08 21878
Module Lead	Stephen Gorard
Level	Masters Level
Credits	20
Semester	Semester 2
Pre-requisites
Co-requisites
Restrictions	MA Social Research
Exclusions
Description	The module introduces students, as appropriate to their research questions and design, to a range of approaches for analysing and handling data. These will include a number of statistical approaches to handling and analysing survey/numeric data, and methodical approaches to analysing qualitative data. It will also normally include reflection some key 'explanatory' variables used in social science such as time, place, sex, class, ethnicity, language and their relevance and how to operationalise them in a range of analyses. The module also emphasises that the method of analysis is not determined by the method of collection. Important topics will include how to judge whether two or more things are different, how to balance analysing according to a plan (or theory) while allowing ideas to emerge from the evidence, the role of judgement in all analysis, and thus the importance of transparently reporting all research decisions (and other good practice in handling data). For analysing large scale survey data, the emphasis is on developing an adequate understanding of statistical principles, descriptive and exploratory methods of analysis (especially graphical methods), operational procedures and interpretations of outputs from statistical packages (such as SPSS). The course is practical rather than particularly technical. An introduction to multivariate analysis will be provided, up to the level of linear regression and analysis of variance. Whilst we shall introduce the use of computer assisted analysis packages (such as NVivo, SPSS), for certain kinds of analysis, the emphasis will be on developing thematic analysis generated by the iterative interplay of theory and data. The need to develop cogent theoretical explanations for findings and the ability to present them appropriately will be emphasised throughout the module.
Learning Outcomes	On completion of the module, students are expected to: Have a sound understanding of the role of data analysis in social research Recognise the importance of a range of data analysis methods and identify which are best suited to address specific research questions or hypotheses Have familiarity with data management skills, preparation, variable coding and recoding, and transcription techniques Know how to generate, extract and interpret data from computer generated outputs and thematic analyses Be familiar with the basic principles and assumptions of descriptive and inferential statistical methods and qualitative initial descriptive reports To understand the role and limitations of tests of statistical significance., i.e. an appreciation of the difference between theoretical and statistical significance Know how to develop main and sub-themes in qualitative analysis Develop an awareness of the role of reflexivity in developing theoretically informed analysis Appropriately able to apply statistical methods to their research questions drawing on both descriptive and multivariate analysis Know how to report and present research findings as related to theoretical frameworks
Assessment	21878-01 : Essay : Coursework (100%)
Assessment Methods & Exceptions	3,000 word essay/project drawing on methods and approaches used during the course.
Other	None
Reading List