In:
PS: Political Science & Politics, Cambridge University Press (CUP), Vol. 55, No. 3 ( 2022-07), p. 605-609
Kurzfassung:
Computational methods have become an integral part of political science research. However, helping students to acquire these new skills is challenging because programming proficiency is necessary, and most political science students have little coding experience. This article presents pedagogical strategies to make transitioning from Excel, SPSS, or Stata to R or Python for data analytics less challenging and more exciting. First, it discusses two approaches for making computational methods accessible: showing the big picture and walking through the workflow. Second, a step-by-step guide for a typical course is provided using three examples: learning programming fundamentals, wrangling messy data, and communicating data analysis.
Materialart:
Online-Ressource
ISSN:
1049-0965
,
1537-5935
DOI:
10.1017/S1049096521001815
Sprache:
Englisch
Verlag:
Cambridge University Press (CUP)
Publikationsdatum:
2022
ZDB Id:
123834-6
ZDB Id:
2049336-8
SSG:
3,6
