qs101 introduction to quantitative methods n.
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  1. QS101 – Introduction to Quantitative Methods in Social ScienceWeek 3: Conceptualisation, Operationalisation and MeasurementFlorian ReicheTeaching Fellow in Quantitative MethodsCourse Director, BA Politics and SociologyF.Reiche@warwick.ac.uk

  2. THEORY

  3. Theory Research Questions Concepts New theory Case Selection Data analysis Data collection The Research Labyrinth

  4. 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?

  5. Examples of Concepts Social Class Agency Inequality Lifestyle Structure Academic Achievement Culture Democracy Gender Teacher Expectations Religious Orientation Leadership

  6. 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)

  7. The Tree-Metaphor Indicator Attribute Concept

  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

  9. 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

  10. 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)

  11. 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

  12. 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

  13. EXAMPLE

  14. 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

  15. 1960s / 1970s: Beyond GDP • Poverty • Unemployment • Inequality  Redistribution from growth

  16. Poverty: Brainstorming • Poverty Line • Headcount / Headcount Index • Total Poverty Gap • Average Poverty Gap • Sen Index • Foster-Greer-Thorbecke Measure • Human Poverty Index

  17. Inequality: Brainstorming • Gini Coefficient • Lorenz Curves • 20:20 ratio • 10:10 ratio • 20:40 ratio (Kuznets ratio) • Theil Index / Atkinson Index

  18. 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

  19. Population Growth Health Inequality Education Poverty GDP Economic Development

  20. Birth Infant Mortality Life Expectancy At 60 Health Economic Development

  21. More to come

  22. ASSESSMENT

  23. 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:

  24. Report Content • Your report will consist of two components. You can handle these separately, or combine them, depending on what suits your argument best. • 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.)

  25. Report Content (contd.) • Be sure to include references to the relevant literature in this discussion. • 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.

  26. Submission • Deadline: 03.12.2014 • Don’t forget to submit on tabula, not anywhere else. • See UG handbook for more details.