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Sampling and Survey Design

Learning objectives

• knowledge of approaches for collecting statistical data, ability to describe and apply these approaches
• knowledge of advantages and disadvantages of certain survey types
• knowledge of design and implementation of surveys and ability to apply this knowledge
• ability to recognize and to justify which method is to apply in which situation, ability to critically question the applicability and to autonomously perform small adaptations

Contents

• schematic process of scientific research project
• statistical design of experiments (particularly idea, experiment, experimental design; factors and factor effects; screening, modelling, and optimization; specific designs)
• sampling methods (particularly random based vs. nonrandom based sampling; representativeness; simple random sampling, stratified and clustered sampling; sample size; bounded prediction)
• survey types (particularly face-to-face, written, via telephone, via internet; characteristics of basic types, advantages and disadvantages)
• questionnaire design (particularly question types, operationalization, answer defaults; objectivity, reliability, validity; Likert scales; layout; the problem of sensitive topics; privacy protection)
• aspects of performing surveys (particularly pretesting; interviewer training, dealing with nonresponse)

Prerequisites

none

Lecture and exercise documents

Script, exercises, sample solutions as well as a collection of formulas are available for download in Stud.IP in the respective semester. Examinations with sample solutions from previous semesters can be found at the end of this page.

Scope and evaluation

• lecture with 2 WCH and exercise with 1 WCH
• written exam
• 5 credit points

Dates

Lecture and exercise dates are announced via Stud.IP. The course takes places every second winter semester. Examination dates can be found on the website of the examination office.

Downloads

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