Contextualising the Teaching of Statistics in Political Science

Teaching Quantitative Methods: Getting …, 2011

The teaching of quantitative research methods is an integral part of most postgraduate programmes in politics, but less common at undergraduate level. This article explores the extent to which research methods in general, and quantitative research methods in particular, form part of the curricula of Politics departments in the UK. We then discuss an approach for motivating interest in a subject that tends to be unpopular with many students. We recommend an approach that utilises the links between the general quantification of politics with the quantitative study of political phenomena, as well as a combination of basic research methods for all and more advanced student-focused training for some.

2004

The methodological pluralism of the political science discipline presents unique challenges to the design of an introductory research methods and statistics course. Conventional approaches to social science statistics education stress statistical concepts and applications that are often of little practical use to students in their subsequent coursework or careers.

International Journal of Mathematical Analysis and Modelling , 2022

The desire of every citizen of a nation is to have overall development. This can only be achieved through implementation of government policies and programmes which are offshoot of research results. In most cases, persons found on the corridors of power neglect results of this research which is the bedrock of development. This paper made use of statistical theories and methods to ascertain if the claim in some quarters that the poor performance of statistics students in political and social sciences related courses is the cause of the political apathy among statisticians which has paved the way for people who have no regard or importance of research which is the walk path to sustainable development to dominate the political space. An analysis of variance for categorical data (catanova) was used in carrying out the test. The statistical findings were based on the result of GST211 (politics, peace studies and conflict resolution) course of students of department of statistics, computer science and agricultural economics of the Federal University of Lafia, Nasarawa state, Nigeria. It was discovered that students of the department of statistics performed worst among the three departments that took the course thereby justifying the claim that poor performance in political and social science related courses is the cause of political apathy among statisticians. The researchers therefore recommend for aggressive enlightenment by lecturers of the department of statistics among their students on the need to develop high interest in political and social science related courses so as to increase political participation of statisticians in order to bring more statistician to the corridor of power for the implementation of the research results rather than turning out research results that are never implemented.

Course Abstract by: Bernhard Kittel This outline is for a course I attended. The course provided a concise introduction to fundamental ideas of descriptive and inferential statistics with the intention to help participants understanding and applying the logic of quantitative analysis in political and social science. It covers the basic concepts of statistics, probability, and test theory. Methods of bi-variate analysis were discussed for nominal, ordinal, and interval-scaled variables, and the basic idea of linear regression analysis were introduced. This course introduced students to using the system ‘R’ as part of its practical application of the course material covered. For more information, please refer to the attached pdf document from ECPR and the lecturer which contains the course syllabus information provided on the course website. No copyright infringement intended.

PS: Political Science & Politics, 2018

ABSTRACTAlthough research methods and statistics play an increasing role in political science and beyond, students all too often find statistics classes intimidating and boring. This need not be the case, however, because statistics classes provide opportunities to pose and answer questions about which students care. This article highlights four steps to making our methods and statistics classes more engaging and meaningful.

1986

This article identifies a set of serious theoretical mistakes appearing with troublingly high frequency throughout the quantitative political science literature. These mistakes are all based on faulty statistical theory or on erroneous statistical analysis. Through algebraic and interpretive proofs, some of the most commonly made mistakes are explicated and illustrated. The theoretical problem underlying each is highlighted, and suggested solutions are provided throughout.

The Philosophy and Methods of Political Science, 2016

The course is based around my new book of this title and also extends into the field of professional practice. Sessions are based around chapters of the book, though I might cover the ground in a slightly different order from the book. Students are advised to read the book before the course so that the material is relatively familiar and can be discussed more easily. Supplementary reading is suggested at the end. This is provided for students to follow up on topics. The course is designed to examine explanation in political science and foster careful consideration of what types of method are appropriate for different research questions. It does not teach research methods as such. I do not teach any specific qualitative or quantitative techniques, but rather explore what we can do with different methods. The readings below are not required for the sessions; rather they enable students to follow up on topics. A more comprehensive list can be provided. Expectations are what students are expected to comprehend after the relevant session. READING Students should read the relevant chapters of Keith Dowding, The Philosophy and Methods of Political Science, London: Palgrave, 2016 before the course. The reading below is not required, but any reading prior to the course will be helpful. These suggestions are to enable students to follow up on topics that take their interest and as it is useful for their own work.

Statistical Journal of the IAOS