Prospectus

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Master Thesis

Course
2019-2020

Admission requirements

  • To start the preparations of the thesis (the proposal) the student should have 48EC of the programme.

  • To carry out the proposal, the student should have obtained 74 EC from the programme.

  • To sit the final examination, the student should have obtained 96 EC from the programme.

Description

The Master Thesis Projects consists of two parts: The Master Thesis Proposal (4 EC), and the carrying out of the proposal for, preferably, ±14 weeks of fulltime study (20 EC).

The Master Thesis proposal is written by the student, but under supervision and based on a clearly defined research aim of the supervisor(s). The proposal includes

  • a concise description of the research aims motivated by the discussion of at least one main scientific publication;

  • a concise description of the research activities, with a detailed time schedule indicating how much time will be invested in each activity: How was 4EC spent on the research proposal? How will 20 EC be spent on the thesis? (and if combined with an internship, how is the 10 EC spent on the internship?). Where there any academic skills the student improved?

  • the statement that the supervisors and student will apply good scientific practices, that follow the University Academic Integrity Regulations and the Ethical Guidelines from Statistical Practice.

The carrying out of the proposal of the Master Thesis will take place under supervision for a duration of the remaining ±14 consecutive weeks of fulltime study.

The goal for student in the Master Thesis project is to produce an academic manuscript of the students’ original work that must be of an academic level. Thus, possibly with additional work, parts of the Master Thesis should have the potential to contribute to (parts of) a peer-reviewed scientific publication.

Learning Outcomes

  • to achieve an understanding of statistical science as a branch of science and not merely a collection of techniques;

  • to obtain a deeper knowledge of statistical methods in a specific chosen area of application, and the familiarity with directions of the current research topic in statistical science and data science;

  • to apply knowledge and understanding in a critical, creative, independent, systematic approach to model and evaluate complex phenomena, which involves the planning and executing of tasks with appropriate methods within a given time frame;

  • to be able to communicate with colleagues and to be able to present clearly, verbally as well as in writing, one’s own research results;

  • take responsibility to develop one’s own competence.

Assessment Method

The student should have fullfilled the following requirements (for Pass/ Fail):

  • Presentation of the Thesis Proposal in a Working Group

  • Peer Reviews of Two Thesis Proposals

  • Attendance at the "preparation for the internship and thesis" lecture.

For the final grade, the student's accomplishments are weighted as follows:

  • 50% of the grade is based on the written Master Thesis (including the appendices)

  • 30% of the grade is based on the general working attitude during the thesis project

  • 10% of the grade is based on the final presentation of the Master Thesis.

  • 10% of the grade is based on the defence of the Master Thesis

The defence of the Master Thesis is to be understood as the Final Examination according the Course and Examination Regulations.

Non-Compulsary Literature

  • Blake, G., & Bly, R.W. (1993). The Elements of Technical Writing. Logman Publishers: New York.

  • Higham, N.J. (1998). Handbook of Writing for the Mathematical Sciences. Society for Industrial and Applied Mathematics (SIAM): Phildalephia, USA.

  • Strunk, W., & White, E.B. (1999) The Elements of Style. S.I: Longman.

Contact information

Maarten Kampert: thesis [at] stat [dot] leidenuniv [dot] nl

Remarks

The blackboard module of the Master thesis is shared with that of the Internship under the name "Internship and Master Thesis [2019-20] 4433MIT34-1920FWN".