# Inferential Statistics

Vak
2020-2021

This course is only available for students in the BA Urban Studies programme. Students need to have passed Introduction to Methodology.

## Description

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 results of an appropriate test. Students will acquire skills in working with statistical software used for these tests.

## Course objectives

• 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 and proportions for one-sample designs.

• Introduction of the t-test for testing hypotheses about means and proportions 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.

## Timetable

Visit MyTimetable.

## Mode of instruction

• Online meetings (compulsory attendance)
This means that students must attend every tutorial session of the course. If a student is unable to attend a tutorial or lecture, 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 by an additional assignment. If they are absent from a tutorial without a valid reason, they can be excluded from the final exam in the course.

• e-Learning modules

## Assessment method

### Assessment

• Weekly assignments covering theory and skills;

• Two home assignments covering theory, statistical tests, and skills from the literature, e-learning modules, computer practice, and online meetings;

• An exam covering theory, statistical tests, and skills from the literature, e-learning modules, computer practice, and online meetings.

### Weighing

Home assignments 30
Exam 70

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.

### Resit

If the end grade is insufficient (lower than 6.0), or the exam grade is lower than 5.0, or the home assignment grade is lower than 5.0, there is a possibility of retaking one home assignment or the exam, replacing one home assignment grade or the exam grade, respectively.

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.

• Howell, D.C. (2016). Statistical Methods for Psychology Leiden edition. Wadsworth: Cengage Learning.

• Pallant, J. (2016). SPSS Survival Manual (6th edition) Berkshire: McGraw-Hill.

## Registration

Enrolment through uSis is mandatory.
General information about uSis is available on the website

Not applicable.

## Contact

Dr. F.M.T.A. Busing

## Remarks

Passing this course is an entry requirement for the thesis.