Statistics, Sample Survey Methodology, Second Cycle, 5 credits

Learning outcomes

Knowledge and Understanding

After completed studies, the student shall have

• knowledge of different methods for editing collected data and how to adjust for missing data in estimation
• an understanding of how the methods can be used in different situations.

Competence and Skills

After completed studies, the student shall be able to

• apply editing methods
• provide with analyses and estimates based on datasets with potential errors and missing data.

Judgement and Approach

After completed studies, the student shall be able to

• in a critical manner, choose methods for editing and handling of missing data from scientific and ethical aspects.

Content

Review of errors in the sampling frame, measurement errors and nonresponse as sources to estimation errors

Techniques used for detection of errors in survey data

• Editing of survey data containing a few variables
• Editing of survey data containing many variables
• Selective editing
• Using statistical models

Treatment of suspicious measurement errors

• Imputation
• Recontacts with respondents

Estimation under nonresponse in surveys

• Imputation
• Quasi-Randomization
• Direct weighting methods
• Indirect weighting methods using auxiliary variables (calibration)
• Subsampling of nonrespondents

Examinations and grades

Examination, 5 credits (Code: A001)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

In accordance with university regulations on grading systems for first and second-cycle courses and study programmes (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades is to be used: fail (U), pass (G) or pass with distinction (VG). For courses included in an international master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the A to F grading scale is to be used. The vice-chancellor, or a person appointed by them, may decide on exceptions from this provision for a specific course, if there are special grounds for doing so.

The grades used on this course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Modes of assessment

Examination, 5 credits (Code: A001)
Written Examination

For students with a documented disability, the university may approve applications for adapted or other modes of assessment.

For further information, see the university's local examination regulations.

Specific entry requirements

First-cycle courses of 90 credits in Statistics, alternatively first-cycle courses of 30 credits in statistics and 60 credits in mathematics, alternatively first-cycle courses of 60 credits in statistics including 7.5 credits of Statistical theory and 7.5 credits of Regression analysis/Econometrics. The applicant must also have the courses Probability Theory, Second Cycle, 5 credits and Inference Theory, Second Cycle, 5 credits as well as qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations.

Other provisions

The course is given in English.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Reading list and other learning resources

Required Reading

A number of articles from scientific journals, around 300 pages altogether.

Reference literature

Särndal, C-E, B. Swensson och J. Wretman (1992)
Model Assisted Survey Sampling
Springer-Verlag, New York

Tillé, Y.(2020)
Sampling and Estimation from Finite Populations
Wiley series in probability and statistics