Undergraduate Course: Applied Demographic Analysis (SCPL10037)
Course Outline
School | School of Social and Political Science |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
SCQF Credits | 20 |
ECTS Credits | 10 |
Summary | The course will include hands on opportunities to conduct applied demographic analysis using Excel and POPGROUP (the Excel-based industry standard software for demographic projections within the UK). Students will apply demographic methods using real data from UK and overseas. We consider how the study of demographic pattern and process relates to many of the great social policy challenges of the 21st Century (population ageing, overpopulation, migration, population growth/decline, spatial and social unevenness in demographic processes). |
Course description |
Set within the framework of the basic demographic equation (population change = births - deaths +/- net migration) the course unpacks the demographer's tool kit. We consider the derivation, use and interpretation of key measures used in the study of population structure and the components of population change (fertility, mortality and migration) concluding with a look at issues involved in developing population projection at national and sub-national levels. We consider how the study of demographic pattern and process relates to many of the great social policy challenges of the 21st Century
Topics covered on the course include:
The Demographic Equation
Demographic Data
Fertility: Period and Cohort Approaches and Explaining fertility differences: a proximate determinants approach
Mortality: Measuring Mortality and the Life Table [Lecture + Workshop]
Migration: measurement and associated issues
Population Projections
Population projections using POPGROUP
Demographic Case Study
|
Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
|
Co-requisites | |
Prohibited Combinations | |
Other requirements | For those students who are required to take a Quantitative Methods course as part of their degree programme, this course can be counted towards that condition. |
Information for Visiting Students
Pre-requisites | None |
High Demand Course? |
Yes |
Course Delivery Information
Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- understanding of the way demographic pattern and process influence our understanding of changing populations and of related social issues
- knowledge and understanding of the key theory and principles underlying demographic analysis
- ability to calculate and interpret a range of measures for demographic analysis
- the ability to access and use appropriate data sources for demographic analysis
- an ability to use demographic data sources and demographic method intelligently in a range of real world applications
|
Reading List
Specific readings will be given each week but the following can be considered core texts.
Hinde, A. (1998) Demographic Methods. Arnold, London [Fairly mathematical approach]
Holdsworth, C., Finney, N., Marshall, A. and Norman, P. (2013) Population and Society Sage [This undergraduate text does not focus on methods but gives a useful introduction to population topics and theories]
Newell, C. (1994) Methods and Models in Demography Wiley [Good for those new to the subject]
Weeks, J.R. (1999) Population: An Introduction to Concepts and Issues Wadsworth, Belmont [A very readable text]
|
Additional Information
Graduate Attributes and Skills |
accessing and analysing demographic data to develop and support a line of argument and contribute to a policy issue
presenting demographic data and analysis
understanding how demographic data and analysis feeds into social debates
critiquing arguments on social/demographic issues that rely on demographic data and analysis
|
Keywords | Not entered |
Contacts
Course organiser | Dr Alan Marshall
Tel: (0131 6)51 1462
Email: Alan.Marshall@ed.ac.uk |
Course secretary | Mr Euan Morse
Tel: 0131 (6)51 1137
Email: emorse@ed.ac.uk |
|
|