Sampling Theory DL (3385)
  
Coordinating lecturer :Prof. dr. Geert MOLENBERGHS 

Language of instruction : English
Credits: 5,0
  
Period: semester 2 (5sp)
  
2nd Chance Exam1: Yes
  
Final grade2: Numerical
 
Exam contract: not possible
 
Sequentiality
 
   No sequentiality

Content

Key terms/content

survey sampling, survey design, survey analysis, stratification, multi stage sampling, clustering, weighting

Learning outcomes

The student is familiar with survey design and analysis, against the context of other study designs. The focus is on general understanding and application, rather than on mathematical rigour.
The student can design a survey and analyse survey data. The student can select and apply appropriate software tools to this effect.

Aims

Commonly used sample survey designs are studied: random, systematic, multi-stage, and clustered sampling. Their statistical and practical advantages and disadvantages are discussed. The implications for statistical analysis are carefully assessed. Other essential topics include: type of survey (face-to-face, mail, telephone), questionnaire design, and non-response.

The student can recognize and distinguish between the main survey designs and analysis methods. The student can apply these methodes in a realistic setting. The student has a general understanding of the concepts underlaying the various methods. This course contributes mainlyh to the objectives and skills:

Topic-specific competences in own discipline (VEE):

the student should

  1. have insight in the design of studies and the consequences of the design on further analysis (experimental studies, observational studies, survey methodology, )
  2. know the limitations of statistical analyses, take them into account and communicate them
  3. know the professional literature and be able to efficiently collect and evaluate statistical information (journals, book references, internet, )

Cross-disciplinary competences (DCE):

the student should

  1. be able to report clearly and professionally, also in an international context, and understand the criteria and guidelines for scientific reports
  2. be able to plan and finish individual tasks as well as group assignments on time
  3. develop a feeling on how to achieve effective consulting. This includes adjusting to the terminology of the client, clarifying and reformulating scientific questions into understandable statistical procedures, making arrangements on the procedure to follow and formulating clear conclusions


Organisational and teaching methods
Organisational methods  
Distance learning ✔  
Project ✔  
Response lecture ✔  


Evaluation

Semester 2 (5,00sp)

Evaluation method
Written exam50 %
Paper✔
Oral exam50 %
Open questions✔
Presentation✔
Evaluation conditions (participation and/or pass)✔
Conditions All components of the evaluation have to be taken up.
Consequences Students who do not participate in one or more of the evaluation components will receive an X score.
Additional information For the oral part of the exam, the range is [-2;10]. This ensures that students cannot merely pass on the written part, not even if they obtain the maximum score on the written part.

Second examination period

Evaluation second examination opportunity different from first examination opprt
No
Explanation (English)The assignment in the second chance period remains exactly the same, as
well as the format of the oral exam.
 

Recommended course material
 

The course slide set out with a list of primarily books that consitute useful background reading. It is not to be considered compulsory for the course, but it is nice to have in mind, also for future reference.


Learning outcomes
Master of Statistics and Data Science
  •  EC 

    • The student can work in a multidisciplinary, intercultural, and international team.

  •  EC 

    • The student has the habit to assess data quality and integrity. 

  •  EC 

    • The student is an effective written and oral communicator, both within their own field as well as across disciplines.

     
  •  DC 

    • The student is an effective oral communicator in their own field.

     
  •  DC 

    • The student is an effective oral communicator, both within their own field as well as across disciplines.

     
  •  DC 

    • The student is an effective writer in their own field.

     
  •  DC 

    • The student is an effective writer, both within their own field as well as across disciplines.

  •  EC 

    • The student is capable of acquiring new knowledge.

 
  EC = learning outcomes      DC = partial outcomes      BC = evaluation criteria  
Offered inTolerance3
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3   Education, Examination and Legal Position Regulations art.16.9, section 2.