Quantitative Research and R

This four-day course combines a theoretical focus on the concept of “governance” with a methodological focus on indicators of “governance quality.” A central aim of the course is to develop the computing skills needed to construct (and to deconstruct) governance indicators. We will use free, open-source software called R (with RStudio) for the statistical computing. We will discuss governance indicators such as the Mo Ibrahim Foundation’s Index of African Governance and the World Bank’s World Governance Indicators.

The course targets specialists in political science, public administration, public policy, and development studies – for example, lecturers, PhD students, and professional researchers. Some prior exposure to quantitative methods is expected, but no specific experience with statistical computing is required. Participants must bring laptop computers. All software, data, and readings will be provided on USB drives. (At least 1 GB of hard drive space is required for the software installation. All major operating systems – Windows, Mac, and Linux – are supported.)

For newcomers to statistical computing, the course will introduce essential skills such as importing data from spreadsheets, transforming variables using formulas, and aggregating variables into indexes. For more experienced participants with statistical computing but not with R, the course will also introduce R data structures and command syntax so as to provide a starting point for learning how to use R to conduct more advanced analyses.

On the final day of the course, participants will present their own short projects, each consisting either of a data-based critique of an existing governance indicator or of a presentation of a newly calculated governance indicator. Participants are expected to attend all sessions and to complete a few required readings.

Participants: Emmanuel Abokyi, Ghana Institute of Management and Public Administration (GIMPA); Kingsley Agomor, Ghana Institute of Management and Public Administration (GIMPA); Clement Akapame; Sabra Asante, Ghana Institute of Management and Public Administration (GIMPA); Ahenkorah Asiamah, University of Ghana; Samuel Ofosu Awuah, Ghana Institute of Management and Public Administration (GIMPA); Gloria Ofori Boadu, Ghana Institute of Management and Public Administration (GIMPA); Joseph Budu, Ghana Institute of Management and Public Administration (GIMPA); Samuel Harrison Cudjoe, Ghana Anti-Corruption Coalition (GACC); Paul Rex Danquah, Ghana Institute of Management and Public Administration (GIMPA); Joseph Darmoe, Ghana Institute of Management and Public Administration (GIMPA); Eric Worlanyo Deffor, Ghana Institute of Management and Public Administration (GIMPA); Aicha Araba Etrew, Gender Studies & Human Rights; Nene Kuditchar, CDD Ghana; Gameli Kumasi, Ghana Institute of Management and Public Administration (GIMPA); Hilda Mbong, Centre for Indigenous Knowledge and Organizational Development (CIKOD); Dr. Justice Kyei Mensah, Ghana Institute of Management and Public Administration (GIMPA); Brigitte Okley; Nana Tawiah Okyir; Ayane Anthony Sackey, Ghana Institute of Management and Public Administration (GIMPA); Enam Yankah, Ghana Institute of Management and Public Administration (GIMPA)

This short course focuses on the use of multiple regression to analyze empirical relationships in data on politics and governance. Multiple regression remains perhaps the most widely used technique in political science and related fields. The aims of the course are to help participants become more informed and critical “consumers” of studies that use multiple regression, and to equip them to “produce” their own basic regression analyses. Participants will use free, open-source software – R (and the RStudio interface) – which they will install on their own laptops. The course will combine interactive lecture sessions and structured exercises.

The course will be taught at an intermediate level. Ideally participants will have some previous experience using R – for example, having completed one of the introductory UM-ASRI/CDD short courses. The course will include a brief refresher on R, though, and those with a solid grounding in quantitative analysis using other software – especially “command-based” software like Stata or SAS – will also benefit from participating.

Themes to be covered include: How R thinks – a refresher on data and functions in R/RStudio; Thinking about causal and spurious (non-causal) association; The assumptions of the (linear) regression model; Regression and regression diagnostics in R; Interpreting and presenting regression results through simulation using the Zelig package (time permitting)

Participants: Ernest Aboagye, Ghana Institute of Management and Public Administration (GIMPA); Kingsley Agomor, Ghana Institute of Management and Public Administration (GIMPA); Dr. Nana Agyemang Frimpong, Ghana Institute of Management and Public Administration (GIMPA); Dr. Kwaku Ofosu Asare, Ghana Institute of Management and Public Administration (GIMPA); Alpha Ba, Senegal; Victor Boadu, Ghana Institute of Management and Public Administration (GIMPA); Stanley Coffie, Ghana Institute of Management and Public Administration (GIMPA); Paul Rex Danquah, Ghana Institute of Management and Public Administration (GIMPA); Isaac Ofosu Debrah, CDD-Ghana; Kakra Duayeden, CDD-Ghana; Israel Kpekpena, Ghana Institute of Management and Public Administration (GIMPA); Napoleon Kurantin, Ghana Institute of Management and Public Administration (GIMPA); Celso Monjane, Mozambique; Gordon Abeka Nkrumah, University of Ghana; Evelyn Nuvor, Gender Centre; Dr. Jesse Porter, Ghana Institute of Management and Public Administration (GIMPA); Alicia Sabin, CDD-Ghana; Dr. Joseph Taabazuing, Ghana Institute of Management and Public Administration (GIMPA); Dr. Patrick Tandoh, Ghana Institute of Management and Public Administration (GIMPA)

This four-day course introduced academic and professional researchers to the principles of quantitative research. It specifically targeted researchers in fields such as political science and public policy, where opportunities for training in quantitative research tend to be quite limited in Africa. Though no prior knowledge of quantitative methods was assumed, the twenty participants were roughly evenly split between those with some previous training and those without.

A distinctive feature of the course was that all of the software used (R and RStudio) was free and open-source. Participants received USB drives with the software and other course materials and worked on their own laptops. The program emphasized learning by doing. In one assignment, participants imported data from the UNDP’s Human Development Report, ran statistical tables and graphs, and replicated the calculation of the Human Development Index. By the end of the fourth day, all participants (working in pairs) presented short projects, which ranged from analysis of survey data on perceptions of corruption in Ghana to an analysis of trends in Africa’s oil reserves-to-production ratio.

Participants: Dr. Abazaami Joseph, University for Development Studies; Regina Oforiwaa Amanfo-Tetteh, CDD-Ghana; Rabiu K. B. Asante, Department of Sociology, University of Ghana; Josephe Baafi, KNUST/AG University; Dr. Kwabena Barima-Antwi, University of Cape Coast; Janet Serwah Boateng, Institute For Development Studies, University of Cape Coast; Attuquaye Clottey, ISSER, University of Ghana; Kweku Debrah, CDD-Ghana; Dominic Deme-Der, Oxfam; Paul Owusu Donkor, University of Ghana School of Pharmacy; Emmanuel Havi, Economics Department, Methodist University; Linda Kwafo, Ghana Integrity Initiative; Yvonne Lamptey , University of Ghana Business School; Dr. Nelson Obirih-Opareh, Agriculture, Medicine and Environment Division (AME); Lawrence Simpi, Center for Migration Studies, University of Ghana; Antoinette Tsiboe- Darko, ISSER, University of Ghana

Participants: David Nana Adjei, University of Ghana; Emmanuel Adu-Danso, University of Ghana; Daniel Agyapong; Daniel Adotey Akai; Rabiu K.B. Asante; Isaac Owusu Asare, CDD-Ghana; Maxwell Ashon, CDD-Ghana; Mohammed Awal, University of Ghana; Francess Dufie Azumah; Richardson Azunu; Sherry Bempah, KNUST; Victor Boadu; Janet Serwah Boateng, University of Cape Coast; Collins Adu-Bempah Brobbey; Isaac Dsamani; Emmanuel Havi, Methodist University; Achakoma Atong Kennedy; N-L. Kuditchar, University of Ghana; Kumi Larbi, CEPIL; Kwasi Addei Mensah, University of Ghana; Yaw Osei Ofori, Youth Bridge Foundation; Jones Opoku-Ware; Justina Serwaah Owusu; Robert Pwazaga, CDD-Ghana; Maxwell Shon; H.T. Yartey

The aim of this three-day course is to introduce professional researchers working in the field of governance and public policy to quantitative research methods, particularly those based in academic institutions and non-commercial research organizations. The course assumes no prior training in quantitative methods nor in statistical computing. Those who have previously taken an introductory course (perhaps several years ago) will also benefit. All of the software used in the course – mainly R and GNU Emacs – is free and open-source and will be distributed to participants on USB drives.

The rationale for such a course is to begin to address the dearth of quantitative research skills among African researchers working in the fields of governance and public policy. Many researchers in these fields have studied disciplines such as political science and law, which at most African universities provide little or no practical training in quantitative methods. The course will help make participants more informed “consumers” of quantitative research, and it will equip them to be “producers” of simple analyses motivated by their own research interests.

The running example in the course is a two-sample difference-of-proportions analysis. This is arguably the simplest way of analyzing a bivariate relationship. It is broadly applicable and calls upon concepts and skills that recur in more complicated analyses – from coding and recoding, to univariate statistics and graphics, to descriptive measures of association, to statistical inference (confidence intervals and hypothesis tests). The restriction that the “grouping variable” and the “outcome variable” must both be coded dichotomously means that difference-of-proportions is rarely the best way to analyze a bivariate association. Yet it provides a useful “foundational analogy” against which more advanced concepts can be introduced.

The course combines interactive lectures with practical exercises that participants work individually or in pairs. On the first day, before introducing computer applications, participants complete a difference-of-proportions analysis “by hand,” using samples of one hundred observations each, drawn from Afrobarometer data for one country. On the second day, they learn to replicate the analysis for a full national sample using R; then they begin designing their own studies, in which they use the same approach to analyze the relationship between two variables of their choice. On the third day, they complete these analyses and give short presentations of their findings. (A course evaluation and discussion of participant interest will follow.)

Participants: PNK Aborampah, CDD-Ghana; Rhoda Acheampong, CDD-Ghana; Anthony Amoah, Central University, Ghana; Edward Ampratwum, CDD-Ghana; Alex Antwi; Kojo Asante, CDD-Ghana; Maxwell A Ashon, CDD-Ghana; Michael Asiedu; Sherry Bempah, KNUST; Kwesi Boateng, Ghana Anti Corruption Coalition; Edmund Coblah; Ernestina Dankyi; Peter Dwuma, KNUST; Adu Kakra, CDD-Ghana; Nene L Kuditchar, University of Ghana; Mary Kyei; Daphne Lariba Nabila, Legal Resources Center; Mark Obeng; Joseph Ocran; Francis Oppong, CDD-Ghana; Sharon Praku, CDD-Ghana; Anthony Ebow Spio; Regina O A Tetteh, CDD-Ghana; Abdul Mumin Yazeed; Paul K Dzene Yidu; Benedict Yiyugsah, CDD-Ghana

Schedule of Events (PDF) »