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Prospectus

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Analysis of Own Data

Course
2015-2016

Admission requirements

MSc Psychology (research) students with a (almost) completed thesis.

Description

This module takes place at the end of the two-year master program. The course aims at evaluating the thesis process from an ethical, integrity point of view. In the course we will discuss several pitfalls of empirical research. We focus on the design of a study, the various aspects of data analysis, and the writing of the research thesis. Moreover, students write a report about the thesis of another student with a detailed, critical scrutiny of the thesis process. In order to write this report the students will interview each other about the various aspects of empirical research and how these were operationalized in the thesis project.

Course objectives

The student learns to look critically at his/her own research practices and those of others.
The students will learn to look beyond standard practices.

Timetable

The timetable will be available as of 1 July 2015.

Registration

Course

Students need to enroll for lectures (and work group sessions). Please consult the instructions for registration.

Elective

Students have to enroll for each elective course separately.

Exchange/Study abroad

For admission requirements contact your exchange coordinator.

Examination

Students are not automatically enrolled for an examination. They can register via uSis from 100 to 10 calendar days before the date; students who are not registered will not be permitted to take the examination.

Mode of instruction

6 lectures of 2 hours

Assessment method

The assessment is based on a two written reports and an exam. The final grade is a weighted average of the three grades (exam 40%, 1st report 40%, 2nd report 20%). All grades should be > 4.

The Faculty of Social Sciences has instituted that instructors use a software programme for the systematic detection of plagiarism in students’ written work. In case of fraud disciplinary actions will be taken. Please see the information concerning fraud.

Reading list

P.I. Good and J.W. Hardin (2012, 4th edition). Common errors in statistics (and how to avoid them), Hoboken, NJ: John Wiley & Sons.

Contact information

Prof. dr. Mark de Rooij
rooijm@fsw.leidenuniv.nl