Performance in the course will be assessed as follows:
Midterm exam: 25%
Group project: 30%
Final exam: 45%
No material other than a dictonary may be used in the final exam.
In total, a minimum of 50 percent needs to be attained to pass the course. The grading system is the following: 0 to 49% - grade 5, 50 to 59% - grade 4, 60 to 69% - grade 3, 70 to 79% - grade 2, 80 to 100% - grade 1. Students who fail must repeat the entire course (and must register in the usual way next time the course is offered). No opportunities for make-ups will be offered.
The midterm exam is based on the topics covered in sessions 1 to 5 and the corresponding book chapters. The exam typically (but not necessarily) involves a combination of multiple-choice/single-choice questions.
The group project is an assignment conducted by teams of 3 to 5 students and involves the analysis of a dataset as well as the interpretation and the presentation of the relevant results. The grade of the group project takes into account both group and individual performance and is determined by the overall quality of the assignment weighted by the individual contribution of each member to the group project (as determined by peer-evaluation). Thus, a different grade might be awarded to students belonging to the same team. Detailed instructions will be provided in class.
The examinable material of the final exam includes all topics covered in the lectures and the corresponding book chapters. The exam will include questions of different formats (e.g., multiple choice questions and mini cases with open-ended questions).
Required textbook is: Field, A. (2013), Discovering Statistics Using SPSS (4th edition), Sage Publications: London [ISBN: 978-1-4462-4918-5].
Recommended additional textbook is: Diamantopoulos, D. and Schlegelmilch, B. (2000), Taking the Fear out of Data Analysis (2nd edition), South-Western CENGAGE Learning: London [ISBN: 978-1-86152-430-0].