- UCAS course code
- UCAS institution code
BAEcon Accounting and Finance
Year of entry: 2023
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Course unit details:
Essentials of survey design and analysis
|Unit level||Level 2|
|Teaching period(s)||Semester 2|
|Available as a free choice unit?||Yes|
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
6. Introduce a range of UK and international social sciences surveys
By the end of this course, you 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;
Prepare survey data for statistical analysis and understand the basic principles;
Carry out and interpret statistical analyses such as exploratory analysis and testing for
differences and associations taking into account the complex survey design;
Use the statistical software SPSS effectively on social science datasets.
Teaching and learning methods
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 and data sources.
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 will give students hands on experience in the basic exploratory analysis of complex survey data, data manipulation, interpretation reporting 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.
- You will develop your skills in: Problem solving and data analysis; Statistical computing, data handling and data manipulation; Interpreting statistical analysis; Report writing.
Weekly online assessments (x8, 30% of the final mark)
Final written exam (70% 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.
|Scheduled activity hours|
|Practical classes & workshops||10|
|Independent study hours|
|Natalie Shlomo||Unit coordinator|