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QS101 – Introduction to Quantitative
Methods in Social Science
Week 3: Conceptualisation, Operationalisation and
Measurement
Florian Reiche
Teaching Fellow in Quantitative Methods
Course Director, BA Politics and Sociology
[email protected]
THEORY
The Research Labyrinth
Theory
Research
Questions
Concepts
New
theory
Case
Selection
Data
analysis
Data
collection
Research Questions
• Why do people vote and why do they
vote the way they do?
• Why do people support racist and
xenophobic ideas?
• Why are some countries (or people)
more corrupt than others?
• Does Islam have a negative impact on
democracy?
Examples of Concepts
Agency
Social Class
Inequality
Lifestyle
Structure
Culture
Democracy
Gender
Leadership
Religious
Orientation
Academic
Achievement
Teacher
Expectations
What is a concept?
Concepts are the building blocks of theory
and represent the points around which
social research is conducted.
(Bryman, 2012, p. 163)
The Tree-Metaphor
Indicator
Attribute
Concept
Source: Adcock, R.N. and David Collier. 2001. Measurement Validity:
A Shared Standard for Qualitative and Quantitative Research. American
Political Science Review, vol. 95, no. 3, 529-46
Source: Adcock, R.N. and David Collier. 2001. Measurement Validity:
A Shared Standard for Qualitative and Quantitative Research. American
Political Science Review, vol. 95, no. 3, 529-46
An easy task?
• “there is no point in arguing about what
a ‘correct’ definition is” (Guttman, 1994,
p. 12)
• “claims that disputes about how to
specify a concept can be put to rest are
inherently suspect” (Munck and
Verkuilen, 2002, p. 8)
Source: Adcock, R.N. and David Collier. 2001. Measurement Validity:
A Shared Standard for Qualitative and Quantitative Research. American
Political Science Review, vol. 95, no. 3, 529-46
Source: Adcock, R.N. and David Collier. 2001. Measurement Validity:
A Shared Standard for Qualitative and Quantitative Research. American
Political Science Review, vol. 95, no. 3, 529-46
EXAMPLE
Economic Development
• Until the 1950’s and 1960’s: economic
growth
• “Trickle Down” effects
• Countries hit growth targets, but nothing
changed in substantive terms for the
population
1960s / 1970s: Beyond GDP
• Poverty
• Unemployment
• Inequality
 Redistribution from growth
Poverty: Brainstorming
• Poverty Line
– Headcount / Headcount Index
•
•
•
•
•
Total Poverty Gap
Average Poverty Gap
Sen Index
Foster-Greer-Thorbecke Measure
Human Poverty Index
Inequality: Brainstorming
• Gini Coefficient
– Lorenz Curves
•
•
•
•
20:20 ratio
10:10 ratio
20:40 ratio (Kuznets ratio)
Theil Index / Atkinson Index
Other attributes
• Example: HDI
– Longevity: life expectancy at birth
– Knowledge: weighted average of of adult
literacy (2/3) and mean years of schooling
(1/3)
– Standard of Living: real per capita income
…
Population
Growth
Health
Inequality
Education
Poverty
GDP
Economic
Development
Infant
Mortality
Birth
Life
Expectancy
Health
Economic
Development
At 60
More to come
Week Topic
1
(no seminar)
2
Preparation of Field Work
3
Field Work on Campus
4
Building Our Data Set
5
Stata Session: Our University
6
Reading Week
7
The Lottery
8
Use and Abuse of Numbers in the Media
9
Inequality
10
Democracy
ASSESSMENT
Instructions
• Choose a statistical concept you find interesting, and that is
relevant to the social sciences (not democracy or inequality from
the seminars).
• Find a relevant data set.
• Locate relevant variables in your data set.
• Seek approval of the concept, the data set, and selected
variables from your module director. Ensure you have obtained
clearance by 10.11.2014. Do not leave this to the last minute, it
can take a while to find an appropriate concept / data set.
• Write a report of not more than 2,500 words (not including
graphs, tables, figures, or bibliography) according to the
following guidelines:
Report Content
• Your report will consist of two components. You can handle
these separately, or combine them, depending on what suits
your argument best.
1. A discussion of your concept. This should include the
following information:
–
–
–
The relevance of this concept in social science research.
An explanation of the concept to a non-expert.
A review of the extent to which this concept is easy, difficult
or problematic to operationalize and measure. (You may
wish to use examples in Part B to illustrate your discussion
with concrete examples.)
Report Content (contd.)
• Be sure to include references to the relevant
literature in this discussion.
2. A presentation of descriptive statistics of the
variables relevant to your concept. Be sure to
include graphs to visualize the data. Use your
knowledge from the module to select the relevant
statistics and to present / visualise the data as
appropriate Again, use literature to back your
argument up, if necessary.
Submission
• Deadline: 03.12.2014
• Don’t forget to submit on tabula, not
anywhere else.
• See UG handbook for more details.