Quantitative Methods in Social Sciences - JTM046

• Title: Quantitative Methods in Social Sciences
• Czech title: Kvantitativní metody v sociálních vědách
• Guaranteed by: Department of Russian and East European Studies (23-KRVS)
• Faculty: Faculty of Social Sciences
• Actual: from 2021
• Semester: summer
• E-Credits: 6
• Examination process: summer s.:
• Hours per week, examination: summer s.:0/2, Ex [HT]
• Capacity: unknown / 12 (15)
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Teaching methods: full-time
• Teaching methods: full-time
• Note: course can be enrolled in outside the study plan; enabled for web enrollment
• Guarantor: Mgr. Jakub Stauber, Ph.D.
• Teacher(s): Mgr. Jakub Stauber, Ph.D.
• Class: Courses not for incoming students
• Is pre-requisite for: JTM049

Annotation

Last update: Mgr. Jakub Stauber, Ph.D. (05.02.2024)

This introductory course to quantitative methods in social sciences presents basic concepts of statistical analysis of quantitative data. Students will gradually learn about various standard statistical methods and different quantitative research designs. Furthermore, students will understand how these methods are employed by social science researchers in academic articles. No formal training in mathematics is required for this course. Although some mathematical formulas will be presented, these will be kept to a minimum.

Aim of the course

Last update: Mgr. Jakub Stauber, Ph.D. (05.02.2024)

The course aims to provide students with a substantive understanding of the covered concepts and statistical methods. The course should enable students to critically read academic research articles employing quantitative methods and to identify arguments made with the support of quantitative data. The emphasis will be placed on showing how research questions and hypotheses are answered/tested using statistical methods. Furthermore, the course aims to teach students the basics of R software and how to conduct the studied methods with this popular software.

Course completion requirements

Last update: Mgr. Jakub Stauber, Ph.D. (23.02.2024)

Weekly active participation 25%

Participation does NOT only involve attending the seminar; rather, active participation includes involvement in the discussions, small groups and asking questions.

R data.camp assignments 25%

Short online courses covering the basics of quantitative methodology and R functions.

Presentation 25%

A structured presentation, approximately 10 minutes on a quantitative article of your choice. You can select your presentation date on the sign-up sheet in Moodle.

Critique 25%

A critique (DUE June 15^th] of approximately 1000 words on a quantitative article of your choice. The critique is a written assessment of how concepts are presented, the framing and testing of the research question(s) and the author’s overall discussion of the findings.

 

 

Seminar Participation (25%)	Excellent	Good	Mixed	Poor	Unsatisfactory
Attendance   /12
Understanding of key arguments/texts
Argumentation

 

R data.camp assignments (25%)	Excellent	Good	Mixed	Poor	Unsatisfactory
Percentage of max XP

 

Presentation (25%)	Excellent	Good	Mixed	Poor	Unsatisfactory
Content: sets out relevant issues, explains key terms, confident with the material, aids understanding
Structure: logical, easy to follow, provides headings, each section relates to overall purpose
Response to questions: willing to answer questions, actively seeks questions

 

Critique (25%)	Excellent	Good	Mixed	Poor	Unsatisfactory
Contribution to knowledge
Presentation of Research Question
Research limitations considered?
Research (wide base of relevant sources?)
Referencing (sources acknowledged/ systematically referenced?)
Expression (written clearly?)
Organisation (well-structured and easy to follow?)

 

 

More in SMĚRNICE S_SO_002: Organizace zkouškových termínů, kontrol studia a užívání klasifikace A–F na FSV UK.

Literature

Last update: Mgr. Jakub Stauber, Ph.D. (05.02.2024)

Bryman, Alan. 2012. Social Research Methods. 4th ed. Oxford ; New York: Oxford University Press.

Thulin, Måns. 2021. Modern Statistics with R. http://www.modernstatisticswithr.com/.

Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. First edition. Sebastopol, CA: O’Reilly.