210015 UE BAK 4 Quantitative Methods of Empirical Social Research (2023W)
(engl.)
Continuous assessment of course work
Labels
ON-SITE
Eine Anmeldung über u:space innerhalb der Anmeldephase ist erforderlich! Eine nachträgliche Anmeldung ist NICHT möglich.
Studierende, die der ersten Einheit unentschuldigt fernbleiben, verlieren ihren Platz in der Lehrveranstaltung.Achten Sie auf die Einhaltung der Standards guter wissenschaftlicher Praxis und die korrekte Anwendung der Techniken wissenschaftlichen Arbeitens und Schreibens.
Plagiierte und erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis).
Die Lehrveranstaltungsleitung kann Studierende zu einem notenrelevanten Gespräch über erbrachte Teilleistungen einladen.
Studierende, die der ersten Einheit unentschuldigt fernbleiben, verlieren ihren Platz in der Lehrveranstaltung.Achten Sie auf die Einhaltung der Standards guter wissenschaftlicher Praxis und die korrekte Anwendung der Techniken wissenschaftlichen Arbeitens und Schreibens.
Plagiierte und erschlichene Teilleistungen führen zur Nichtbewertung der Lehrveranstaltung (Eintragung eines 'X' im Sammelzeugnis).
Die Lehrveranstaltungsleitung kann Studierende zu einem notenrelevanten Gespräch über erbrachte Teilleistungen einladen.
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from We 06.09.2023 08:00 to We 20.09.2023 08:00
- Registration is open from Fr 22.09.2023 08:00 to We 27.09.2023 08:00
- Deregistration possible until Fr 20.10.2023 23:59
Details
max. 35 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Thursday 05.10. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 12.10. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 19.10. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 09.11. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 16.11. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 23.11. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 30.11. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 07.12. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 14.12. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 11.01. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 18.01. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
- Thursday 25.01. 13:15 - 14:45 Seminarraum 6 UniCampus Hof 7 Eingang 7.1 OG01 2H-O1-33
Information
Aims, contents and method of the course
Assessment and permitted materials
The final assessment will be based on the following components:
- Attendance/Participation (10% of final grade): regular attendance in class (maximum 2 classes can be missed)
- 5 short homework assignments (25% of final grade) based on materials in the course texts. Students are encouraged to form study groups but assignments must be completed individually. The Turnitin program will ensure that no plagiarism occurs.
- 1 short test (25% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata output. Duration: max 45 minutes.
- Final assignment (40% of final grade). At the end of the course, you will be required to write a final paper of 2000-2500 words, focusing mostly on methods with applications in Stata. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course. Joint work is NOT allowed for the final assignment. The Turnitin program will ensure that no plagiarism occurs.
Deadline for handing in the final assignment: 29 February 2024.
Final grades will be a summation of these:
- 100-87 Points Excellent (1)
- 86-75 Points Good (2)
- 74-63 Points Satisfactory (3)
- 62-50 Points Sufficient (4)
- 49-0 Points Insufficient (5)
- Attendance/Participation (10% of final grade): regular attendance in class (maximum 2 classes can be missed)
- 5 short homework assignments (25% of final grade) based on materials in the course texts. Students are encouraged to form study groups but assignments must be completed individually. The Turnitin program will ensure that no plagiarism occurs.
- 1 short test (25% of final grade). The test will be conducted in class and will concern theoretical questions and/or interpretation of Stata output. Duration: max 45 minutes.
- Final assignment (40% of final grade). At the end of the course, you will be required to write a final paper of 2000-2500 words, focusing mostly on methods with applications in Stata. Detailed instructions about the final assignment will be posted on Moodle and circulated in class before the end of the course. Joint work is NOT allowed for the final assignment. The Turnitin program will ensure that no plagiarism occurs.
Deadline for handing in the final assignment: 29 February 2024.
Final grades will be a summation of these:
- 100-87 Points Excellent (1)
- 86-75 Points Good (2)
- 74-63 Points Satisfactory (3)
- 62-50 Points Sufficient (4)
- 49-0 Points Insufficient (5)
Minimum requirements and assessment criteria
Please note that all four components are essential for the final grade, i.e. regularly attend classes, hand in 5 homework assignments, complete the short test, and submit the final assignment. In cases of suspected plagiarism, you may be called upon to reasonably demonstrate that any work they you have submitted is your own (the anti-plagiarism software Turnitin will be used via Moodle to detect plagiarism). A passing grade on each component is not required for a passing grade in the course.
Examination topics
The examination will focus on different topics covered in class and will include basic data analysis using the Stata commands learnt in class. Detailed instructions about the homework, the test and the final assignment will be shared on Moodle in due time.
Reading list
Main textbook:
- De Mesquita, E. B., & Fowler, A. (2021). Thinking clearly with data: A guide to quantitative reasoning and analysis. Princeton University PressRecommended Texts:
- Philip H Pollock III and Barry C. Edwards. (2018). A Stata® companion to political analysis. CQ Press/SAGE Publications
- Kyle C. Longest. (2019). Using Stata for quantitative analysis. SAGE Publications
- Paul M. Kellstedt, and Guy D. Whitten. (2018) (3rd edition). The fundamentals of political science research. Cambridge: Cambridge University Press
- Paul M Kellstedt and Guy D. Whitten. (2019). A Stata Companion for the Third Edition of The Fundamentals of Political Science Research. Cambridge University PressSupplementary materials:
- Alan C. Acock. (2014). A Gentle Introduction to Stata (6th edition). College Station, Texas: Stata Press
- Alan Agresti. (2018). Statistical methods for the social sciences (5th edition). New Jersey: Pearson Education International
- Donald J. Treiman. (2009). Quantitative Data Analysis. Doing Social Research to Test Ideas. San Francisco: Jossey-Bass
- De Mesquita, E. B., & Fowler, A. (2021). Thinking clearly with data: A guide to quantitative reasoning and analysis. Princeton University PressRecommended Texts:
- Philip H Pollock III and Barry C. Edwards. (2018). A Stata® companion to political analysis. CQ Press/SAGE Publications
- Kyle C. Longest. (2019). Using Stata for quantitative analysis. SAGE Publications
- Paul M. Kellstedt, and Guy D. Whitten. (2018) (3rd edition). The fundamentals of political science research. Cambridge: Cambridge University Press
- Paul M Kellstedt and Guy D. Whitten. (2019). A Stata Companion for the Third Edition of The Fundamentals of Political Science Research. Cambridge University PressSupplementary materials:
- Alan C. Acock. (2014). A Gentle Introduction to Stata (6th edition). College Station, Texas: Stata Press
- Alan Agresti. (2018). Statistical methods for the social sciences (5th edition). New Jersey: Pearson Education International
- Donald J. Treiman. (2009). Quantitative Data Analysis. Doing Social Research to Test Ideas. San Francisco: Jossey-Bass
Association in the course directory
Last modified: We 13.11.2024 12:06
Students will learn the basic “tools” to conduct quantitative data analysis, using the statistical software Stata. Theoretical concepts of descriptive and inferential statistics will be briefly discussed in class, in combination with their practical application using existing databases typical of those in the field of political science. By the end of the course, you should be able to describe a dataset and conduct basic inferential analyses using the main commands implemented in Stata.
At the end of the course, students should know and understand the basic methods and simple statistical procedures in the social sciences, as well as be able to interpret and evaluate the results of quantitative social research in research and the media. You should also be able to develop questions yourself and answer them using quantitative methods and be able to present the results of quantitative research appropriately.
Please note that the course will be instructed in English. This requires that class discussions, weekly assignments, written tests and the term paper are completed in English.