Course description
This course is intended for students with some prior introduction to basic quantitative methods in the social sciences. Statistics 2 follows Statistics 1, which students are assumed to have taken in the previous block. The emphasis in this course lies on applied quantitative analysis (linear and logistic regression). The course first briefly reviews statistical inference, and then covers simple linear regression, multiple linear regression, the use of interaction effects and dummy variables, and binary and multinomial logistic regression. We will also discuss how inference and estimation should and should not be used in social science research. Students will continue to familiarise themselves with the software programme SPSS. A more detailed weakly programme will be announced via Brightspace.
Course objectives
This course provides students with a foundation in further quantitative analysis as used in political science research.
This course helps students gain further skills in using software for quantitative analysis.
Upon successful completion of this course, students should be able to employ and interpret, as well as critically evaluate others’ use and interpretation of, a number of more advanced statistical analyses.
Mode of instruction
This course is taught through a combination of one weekly lecture and one weekly seminar. The lectures introduce students to applied quantitative analysis and follow the course textbook. In seminars, students will familiarise themselves with SPSS and apply the concepts and methods taught in the lecture. These seminars will take place in computer rooms. Students are required to prepare assignments and submit these before class via Brightspace/Turnitin.
Course materials
This course uses blackboard. Other required course materials are the course textbook and the SPSS software.
Field, Andy (2018) Discovering Statistics using IBM SPSS Statistics (5th edition). London: Sage. ISBN: 9781526419521.
Students need to purchase SPSS Statistics 25 via SURF
Assessment
Assessment for this course consists of a combination of coursework (timely submission of assignments and participation in seminars, totalling 10%) and one or more written tests including a final written exam (totalling 90%). More details on assessment will be provided via Blackboard at the start of the course.
Attention: you need to enroll before the deadline via uSis to take the final written exam! You are required to obtain at least a grade of 5.0 on the final written test to pass the course. If you obtain a final “fail” course mark you can only resit the final written exam. Smaller elements such as coursework or smaller tests cannot be retaken.
The time and location of inspection and debriefing of the exam will be announced via Blackboard no later than the publication of the grades.
Brightspace
This course uses Brightspace. Students are required to check the course page regularly for announcements, course materials and to submit assignments.
Registration
See general information on Tab 'Year 1'.