BASS Social Anthropology and Sociology

The unit aims to:  

1. Provide an overview of the process of survey planning, design, management, estimation and   
    analysis of complex survey data  

2. Introduce the key decisions in survey design, including research ethics  

3. Introduce methods of random sampling and calculating sample size  

4. Present the design and testing of questionnaires 

5. Introduce examples of inference, including calculating and using survey weights in statistical  
    modelling 

6. Introduce a range of UK and international social sciences surveys 

• On completion of this unit, successful students will be able to
• Understand the main requirements and problems of planning, designing and implementing a sample survey (including sampling methods, drawing a random sample, designing questionnaires, sample size calculations) and apply these to specific research questions; 
• Describe a few major UK and international surveys from the past few decades;
• Distinguish between different sampling designs;
• Choose the sampling design that is most appropriate to a given research question;
• Prepare survey data and apply basic statistical methods that are appropriate for different sampling designs;
• Use the statistical software R effectively on social science datasets;
• Identify the steps of questionnaire design, implementation and testing;
• Assess the quality of a survey (considering errors, biases and nonresponse);
• Discuss the key ethical issues in survey research;
• Draft a survey report.
   

The course will involve: lectures, group work in tutorials and computing lab classes. Extensive use will be made of relevant on-line resources where students can learn about social science data. Please note the information in scheduled activity hours are for guidance only and may change.
Blackboard resources will be used to enable students to access teaching data, data sources and supplementary learning material.
The lecture component will provide a theoretical and methodological framework for learning about the design of surveys and analysis of survey data. Group work in the tutorials will give students hands on experience on the design and implementation of a survey. Practical sessions in the computing lab (using the R software package) will give students hands on experience in the basic exploratory and statistical analysis of complex survey data, data manipulation, interpretation of   results. Such skills are highly transferable.
The emphasis on the use of real data to answer real questions is designed to engage students and enable students to consider using such approaches as part of their own dissertation research.
 

Weekly online assessments (x10, 10% of the final mark), 
Three quizzes (x3, 24% of the final mark),
Final written exam (66% of the final mark

All Social Statistics courses include both formative feedback - which lets you know how you're getting on and what you could do to improve - and summative feedback - which gives you a mark for your assessed work.  

Specific readings are listed for each week.   

A Part 1 of the module: Design of Surveys 

1. Czaja, R. and Blair, J. (2013) Designing Surveys: a guide to decisions and procedures.  
3rd ed. Sage, London. 

2. De Vaus, D. (2002) Surveys in Social Research. 5th ed. Routledge, London.   

3. Fowler, F. J. (2013) Survey Research Methods, 5th edition. Sage, California. 

4. Groves, R M et al. (2009) Survey Methodology, 2nd Edition. J. Wiley, Hoboken.   

5. Oppenheim, A.N. (2000) Questionnaire Design, Interviewing and Attitude Measurement  
New Edition. Bloomsbury Academic, London.    

B Part 2 of the module: Statistical analysis 

1. I. Diamond and J. Jefferies (2001).  Beginning Statistics: an Introduction for Social Scientists, London: Sage.    

2. A. Field (2013).  Discovering Statistics using SPSS, 4th Edition, London: Sage.   

3. P. R. Kinnear and C. D. Gray (2006).  SPSS for Windows Made Simple: Release 12.0, Hove: Psychology Press. 

4. L. Jaisingh (2005).  Statistics for the Utterly Confused, 2nd Edition. McGraw-Hill.