Introductory description

A vast amount of political research is quantitative, and even if you decide never to conduct quantitative analysis yourself, you will find an introductory level of knowledge in quantitative methods useful to critically engage with your discipline as a whole. Skills in data analysis are also crucial for finding employment in graduate level jobs; the Institute of Student Employers found in its 2018 report that "data analysis" is amongst the 5 most important skills employers wish graduate students to have. This module will deliver an introduction to quantitative political analysis. It is based on Reiche's typology of Quantitative Methods, and explores each of its tasks (conceptualisation and measurement, numerical data, data analysis and interpretation) at an introductory level. The module uses the software R.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Introduction to Quantitative Methods in Political Analysis

I. CONCEPTUALISATION AND MEASUREMENT

1. Conceptualisation and Measurement

2. Conceptualisation and Measurement in the Real World

II. NUMERICAL DATA

1. Exploration of Single Variables

2. Levels of Measurement and Distributions

3. (Reading Week)

III. DATA ANALYSIS AND INTERPRETATION

1. Sampling Distributions and z-Scores

2. Confidence Intervals and the t-Distribution

3. Sample Size and Statistical Inference

4. Introduction to Causality

Learning outcomes

By the end of the module, students should be able to:

• Apply the tasks of Quantitative Methods to substantive politics research problems
• Understand the basic principles of conceptualisation and measurement in political science
• Analyse core descriptive statistics, by hand and through the software R
• Understand the basic principles of causality
• Understand the principles of statistical inference

Indicative reading list

• Adcock, R., & Collier, D. (2001). Measurement Validity: A Shared Standard for Qualitative and Quantitative Research. American Political Science Review, 95(3), 529-546.

• Agresti, A. (2018). Statistical Methods for the Social Sciences (Fifth ed.). Harlow: Pearson.

• Ake, C. (1993). The Unique Case of African Democracy. International Affairs, 69(2), 239-244.

• Brady, H. E. 2011. Causation and Explanation in Social Science. In R. Goodin (Ed.), The Oxford Handbook of Political Science. Oxford University Press.

• British Election Study. (2020). British Election Study. available online at https://www .britishelectionstudy.com/data/.

• Clark, T., Foster, L., & Bryman, A. (2021). Bryman’s Social Research Methods (Sixth ed.). Oxford: Oxford University Press.

• Dasgupta, P. (1993). An Inquiry Into Well-Being And Destitution. Oxford: Oxford University Press.

• European Commission. (n.d.). Eurostat – Your Key to European Statistics. available online at https://ec.europa.eu/eurostat/data/database.

• Frankfort-Nachmias, C., Nachmias, D., & DeWaard, J. (2008). Research Methods in the Social Sciences (Eighth ed.). New York: Worth Publishers.

• Huff, D. (1991). How to Lie with Statistics. Penguin.

• Jerven, M. (2011). Users and Producers of African Income: Measuring the Progress of African Economies. African Affairs, 110(439), 169-190.

• King, G. (1995). Replication, replication. PS: Political Science and Politics, 28(3), 541-559.

• Munck, G. L., & Verkuilen, J. (2002). Conceptualizing and Measuring Democracy: Evaluating Alternative Indices. Comparative Political Studies, 35(5), 5-34.

• Perkins, D. H., Radelet, S., Snodgrass, D. R., Gillis, M., & Roemer, M. (2001). Economics of development (Fifth ed.). New York, NY: Norton.

• Reiche, F. (in press). Introduction to Quantitative Methods for the Social Sciences. Oxford: Oxford University Press.

• Republic of Kenya. (1968). Economic Survey 1967.

• Republic of Zambia. (n.d.). National Accounts Statistics GDP Revision of Benchmark 1994 Estimates. Lusaka: Central Statistical Office.

• Rich, R. C., Brians, C. L., Manheim, J. B., & Willnat, L. (2018). Empirical Political Analysis: Quantitative and Qualitative Research Methods. London: Routledge.

• Tufte, E. R. (2001). The Visual Display of Quantitative Information (Second ed.). Cheshire, Conn: Graphics Press.

• UNODC. (2019). Crime Data: Total Prison Population. available online at https://
  dataunodc.un.org/crime/total-prison-population.

• Vanderbilt University Department of Biostatistics. (n.d.). Vanderbilt Biostatistics Datasets. available online at https://hbiostat.org/data//.

• World Bank. (2020). World Development Indicators. available online at https://datacatalog.worldbank.org/dataset/world-development -indicators.

View reading list on Talis Aspire

Research element

Mini Research Project during seminars

International

Data from around the world is used.

Subject specific skills

• Quantitative Research Design
• Basic proficiency in a statistical programme
• Process of Conceptualisation and Measurement and its relevance in political science research
• Calculation of descriptive statistics

Transferable skills

• Written communication skills
• Oral communication skills
• Problem-solving skills
• Skills in the use of information technology
• Skills of interpretation and the critical analysis of primary and secondary sources
• The ability to digest, retain and apply complex information and ideas
• Ability to conduct research and reference your work appropriately
• Time management skills and the ability to meet deadlines
• The ability to reflect critically on the extent and limitations of how and what you have learned, discovered and understood