BAEcon Economics / Course details
Year of entry: 2018
Course unit details:
Unequal Societies - Health, Wellbeing & Happiness
|Unit level||Level 1|
|Teaching period(s)||Semester 1|
|Offered by||Social Statistics|
|Available as a free choice unit?||Yes|
This module will provide an introduction to accessing and using quantitative data and evidence with a focus on health, well-being and happiness. Such skills are in demand in the social research profession across the public and private sector.
After reviewing different data types (relating this specifically to the students own discipline areas where possible), we consider how to access and analyse such data. This in part will include developing the student's critical data skills and will involve hands on training and practice analyses of social survey data using on-line interfaces such as NESSTAR (http://nesstar.esds.ac.uk) and software such as Excel and SPSS.
Lecture Schedule (10 x 2hr lectures)
1.Health, well-being and happiness in the UK. Introduction to quantitative survey and administrative data.
2. Measuring health, well-being and happiness. Key data and variables.
3. Objective and subjective well-being - Understanding survey questions (groups generate example questions)
4. Who lives longest? Looking at individual differences in health, well-being and happiness. Basic statistical skills for data analysis: counts, %s, means, SD, bar charts, histograms, scatterplots.
5. Where do people live longest? Country differences. Comparing across areas and countries. Sampling and inference for survey data.
6. Practical session (1) Key Variables - Excel/NESSTAR workshop (Lab)
7.Analysing survey data. Developing research hypotheses, distributions, confidence intervals, Z scores and testing.
8. Practical session (2) Key Variables - Using SPSS/Excel (Lab)
9. Measurement debate. Data quality issues and survey data - missing data/non- response/satisfycing. Other data sources for measuring health, well-being and happiness.
10. Report writing skills, presenting tables, course overview and assignment
Tutorials (10 x 1hr tutorials)
The tutorials will be linked to each lecture and based around embedding practical skill learning using tasks and group work.
The tutorials will form part of the formative assessment for the course where students present ideas and draft outlines for discussion and feedback. In addition, students will be given the opportunity to do a practice essay and will get feedback on their writing. The essay will be linked to Lectures 7 and 8. Feedback will be given during tutors' office hours in the last week of the semester.
The unit aims to:
(i). To develop the students knowledge of the evidence for understanding inequality in relation to health, well-being and happiness.
(ii). To introduce students to the key analytical skills required and provide basic training in the use of software for analysing quantitative data.
(iii). To develop students understanding of sampling, sample bias and statistical inference in social research.
(iv). To enable students to develop and write a dissertation research proposal based on such data analysis should they choose to in their subsequent years of study.
Student should/will (please delete as appropriate) be able to
Knowledge and Understanding: An understanding of the evidence and debates regarding health, well-being and happiness in the UK and internationally.
Intellectual skills: An understanding of good practices in evaluating evidence and data and assessing scientific robustness. Development of critical skills in evaluating data and methods through: lectures, lab classes, group work and independent reading.
Practical skills: Skills in using social statistics and practical experience of data analysis including using software (Excel/SPSS) and use of on-line tools such as NESSTAR.
Transferable skills and personal qualities: Critical data analysis and evaluation skills will be developed. Social statistics and data analysis skills are in high demand in the labour market. The group work will also aid the student in development of their communication and team working skills.
Teaching and learning methods
The course will involve: lectures, group work and lab classes. Extensive use will be made of relevant on-line resources including: NESSTAR, data archives (ESDS/UK Data Archive, Question Bank) analysis and visualisation tools and literature resources as well as video and radio recordings.
Blackboard resources will be used to enable students to access teaching data and example pilot /test questions on health, well-being and happiness. Other possible options will include: asking students to write their own Blogs during the course. We may also use Blackboard discussions/comments as a form of measuring student participation.
The lecture component will provide a theoretical and methodological framework for learning about how to understand, access and analyse quantitative data. Practical sessions will give students hands on experience in aspects of data analysis and interpretation and in using appropriate software for data manipulation. 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 at a later date.
The course will be assessed by a 2 hour exam (100%). Students will also be required to complete a non-assessed essay and presentation.
Biwas-Diener, R. and Diener, E. (2001): Making the Best of a Bad Situation: Satisfaction in the Slums of Calcutta, Social Indicators Research, 55: pp. 329-352.
Biswas-Diener, R. and Diener, E. (2006): The Subjective Well-being of the Homeless, and Lessons for Happiness, Social Indicators Research, 76: pp. 185-205.
Diamond, I and Jefferies, S. (2005) Beginning Statistics. London: Sage.
Diener, E. and Biswas-Diener, R. (2002): Will Money Increase Subjective Well-being? A Literature Review and Guide to Needed Research, Social Indicators Research 57: pp. 119-169.
Diener, E., Horwitz, J. and Emmons, R. (1985): Happiness of the very wealthy, Social Indicators Research, 16: pp. 263-274.
Field, A. P. (2011) Discovering Statistics Using SPSS London: Sage.
Heiman, G.W. (2004) Essential Statistics Boston: New York.
Inglehart, R. (2002). "Gender, aging, and subjective well-being." International Journal of Comparative Sociology 43(3-5): pp. 391-408.
Everitt, B. and Hay, D. (1992) Talking About Statistics London: Edward Arnold.
Mason, J. and Dale, A. (2011) Understanding Social Research, Sage.
Sen, A. (2005): Human Rights and Capabilities, Journal of Human Development, 6 (2): pp. 151-166.
Wiggins, R. D. (1999). "Indicators of children's well-being." Population Studies - A Journal of Demography 53(3): 388-389.
UK Data Archive www.data-archive.ac.uk/
ESDS - www.esds.ac.uk/government/
Survey Network http://www.surveynet.ac.uk
Nesstar - http://nesstar.esds.ac.uk/webview/index.jsp
Research Methods Centre http://www.ncrm.ac.uk/
Oxford Internet Institute www.oii.ox.ac.uk/
Oxford e Research Centre www.oerc.ox.ac.uk/
Radical Statistics http://www.radstats.org.uk/
|Scheduled activity hours|
|Assessment written exam||2|
|Practical classes & workshops||10|
|Independent study hours|
|Kingsley Purdam||Unit coordinator|