This course is only available for students in the BA Urban Studies programme. Students need to have passed Introduction to Methodology.
In this course students’ knowledge of probability theory will be refreshed, and applied to the statistical tests used most frequently in urban studies and other disciplines. The aim is for students to understand the following concepts: sampling distribution; statistical reliability; hypothesis testing; the principles and procedures for the various significance tests. Students should be able to select, perform, and report the appropriate test in a given situation. Students will acquire skills in working with statistical software used for these tests.
Introduction to inferential statistical procedures by examining the general theory of hypothesis testing and describing specific concepts as they apply to all hypothesis tests.
Introduction to the concept of probability, its rules and applications.
Introduction of the chi-square test for testing hypotheses using categorical, count, or frequency data.
Introduction of the t-test for testing hypotheses about means for one-sample designs.
Introduction of the t-test for testing hypotheses about means for two-sample designs.
Introduction of the estimation of magnitude of differences between means, the calculation and interpretation of effect sizes and the introduction of the concept of power of a statistical test.
The timetable is available on the Urban Studies Website
Mode of instruction
Work group (compulsory attendance)
This means that students have to attend every session of the course. If a student is unable to attend a workgroup, they should inform the lecturer in advance, providing a valid reason for absence. The teacher will determine if and how the missed session can be compensated. If they are absent from a workgroup without a valid reason, they can be excluded from the final exam in the course.
Total course load for this course is 5 EC (1 EC equals 28 hours), which equals 140 hours, broken down by:
Attending lectures and workgroups: 12 x 2 = 24 hours
Preparing for lectures and workgroups: 12 x 6 = 72 hours
Completing assignments: 10 x 2 = 20 hours
Preparing for examination: 2 x 8 = 16 hours
Examination: 6 hours
Exam review: 2 hours
Weekly mandatory assignments covering theory and skills before and after meetings;
Written examination consisting of open questions, covering both theory and statistical calculations from the literature, practical sessions, and the lectures;
A computer skills test covering the various aspects of students’ skills in working with statistical software as well as describing and interpreting analysis output.
|Weekly assignments and computer skills test||30|
To successfully complete the course, please take note that the end grade of the course is established by determining the weighted average of all assessment components.
If the end grade is insufficient (lower than 6.0), or the exam grade is lower than 5.0, there is a possibility of retaking the written examination, replacing the previous exam grade. No resit is available for the assignments or the computer skill test.
Faculty regulations concerning participation in resits are listed in article 4.1 of the Faculty Course and Examination Regulations.
Feedback and inspection
How and when an exam review will take place will be disclosed together with the publication of the exam results at the latest. If a student requests a review within 30 days after publication of the exam results, an exam review will have to be organised.
Blackboard will be used for:
- publication of lecture slides, assignments, instructions and additional materials
Howell, D.C. (2016). Statistical Methods for Psychology Leiden edition. Wadsworth: Cengage Learning.
Pallant, J. (2016). SPSS Survival Manual (6th edition) Berkshire: McGraw-Hill.
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