Undergraduate Module Descriptor

SSI2005: Data Analysis in Social Science 2

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

Module Aims

You will learn the strengths and weaknesses of the OLS regression model from a classical statistics perspective. Using a combination of lectures, practical demonstrations and practical assignments, this module aims at developing your skills in the analysis and presentation of quantitative data. Specifically, you will learn how to construct data sets from individual and aggregate level data, how to analyse these data using the appropriate statistical tools – ranging from simple t tests for the comparison of means to more complex multivariate regression analysis - and how to best display summary statistics and estimation results using relevant techniques for the visual – e.g., graphical - display of data. The module will adopt a “hands on” approach, with particular emphasis on applied data analysis and on computational aspects of quantitative social science research

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 Skills	1. Recognise and evaluate in writing the diversity of specialised techniques and approaches involved in analysing quantitative data in political science, sociology and criminology 2. Use statistical analysis to test research hypothesis 3. Present and summarise analysed data in a coherent and effective manner 4. Demonstrate acquired skills, confidence and competence in a computer package for statistical analysis (e.g. Excel and R)
Discipline-Specific Skills	5. Understand and use the tools and techniques of quantitative research for the analysis of political and social data 6. Use statistical evidence to empirically evaluate the (relative) validity of political, sociological and criminological theories and hypothesis 7. Construct well thought out and rigorous data analysis, tables and reports for both written and oral presentation 8. Examine relationships between theoretical concepts with real world empirical data
Personal and Key Skills	9. Study independently 10. Use IT and, in particular, statistical software packages - for the retrieval, analysis and presentation of information 11. Work independently, within a limited time frame, and without access to external sources, to complete a specified task.

How this Module is Assessed

In the tables below, you will see reference to 'ILO's. An ILO is an Intended Learning Outcome - see Aims and Learning Outcomes for details of the ILOs for this module.

Formative Assessment

A formative assessment is designed to give you feedback on your understanding of the module content but it will not count towards your mark for the module.

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Lab assignments	4 practical exercises using statistical software to solve problems based on material covered in lecture	3-4, 6-8, 10-11	Written

Summative Assessment

A summative assessment counts towards your mark for the module. The table below tells you what percentage of your mark will come from which type of assessment.

Coursework	Written exams	Practical exams
60	40	0

...and this table provides further details on the summative assessments for this module.

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Mid term examination	40	50 minutes	1-9, 11	Written
Final assignment: Guided Data Analysis Essay	60	Equivalent to 3,000 words in total	1-9	Written
	0
	0
	0
	0

Re-assessment

Re-assessment takes place when the summative assessment has not been completed by the original deadline, and the student has been allowed to refer or defer it to a later date (this only happens following certain criteria and is always subject to exam board approval). For obvious reasons, re-assessments cannot be the same as the original assessment and so these alternatives are set. In cases where the form of assessment is the same, the content will nevertheless be different.

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Mid-Term Examination	Final Examination (50 minutes)	1-9, 11	August/September reassessment period
Final Assignment	A data analysis exercise that has students conduct their own data analysis	1-9	August/September reassessment period

Re-assessment notes

Where you have been referred/deferred as a result of failing or not completing the final assignment to enable you to pass that component of the module’s summative assessment, then you will be asked to undertake an alternative written assignment with a data analysis component. This new written assignment will constitute 60% of the final module mark.