Sampling I

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Sampling I - Course Details

Delve into the course contents and find out about the faculty members.

Single Course Price:

800.00 EUR (tax exempt)



Raphael Nishimura, PhD (University of Michigan)

Video lecture:

Raphael Nishimura, PhD (University of Michigan)

Course Dates

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This course is part of the Mannheim Data Science Certificate: Sampling.

Book this course or the entire certificate here!

In order to book the course with alumni conditions, please get in touch with Manon Pfeifer directly.


Course Description

Short Course Description
Sampling is an applied statistics methods course, but differs from most statistics courses because it is concerned almost exclusively with the design of data collection. Little of the analysis of collected data will be discussed in the course. The course will concentrate on problems of applying sampling methods to human populations, since sampling human populations poses a number of particular problems not found in sampling of other types of units. The principles of sample selection, though, can be applied to many other types of populations.

The course is presented at an intermediate statistical level. While we will not develop mathematical aspects of sampling theory, statistical notation and outlines of some algebraic proofs will be given. A sound background in applied statistics, proficiency in mathematics, including basic algebra, is necessary, since some algebraic derivations will be presented (although little emphasis will be placed on the derivations). A thorough understanding of the notation and algebraic results will be required.

Course Objectives
By the end of the course, students will…

  • understand the basic ideas, concepts and principles of probability sampling from an applied perspective
  • be able to identify and appropriately apply sampling techniques to survey design problems
  • be able to compute the sample size for a variety of sample designs
  • understand and be able to assess the impact of the sample design on survey estimates
  • be able to estimate the precision of the survey statistics using different estimation techniques

Course Composition
This is a 4 ECTS course, which runs for 8 weeks. The content of the course is broken down into 8 units:

  1. Introduction; Course Perspectives
  2. Simple Random Sampling, Sampling Frames, and Introduction to Clustering
  3. Stratified Sampling I
  4. Stratified Sampling II, Systematic selection
  5. Cluster Sampling
  6. Unequal-Sized Clusters I
  7. Unequal-Sized Clusters II
  8. Variance Estimation

Learning and Teaching Methods
In this course, you are responsible for watching video recorded lectures and reading the required literature for each unit and then “attending” mandatory weekly one-hour online meetings where students have the chance to discuss the materials from a unit with the instructor. In addition, students are encouraged to post questions about the materials covered in the videos and readings of the week in the forum before the meetings. Just like in an on-site course, homework will be assigned and graded and there will be a final exam at the end of the course.

Grading will be based on:

  • Homework assignments (worth 50% total)
  • Quizzes (worth 15% total)
  • Participation in discussion during the weekly online meetings, submission of questions via e-mail demonstrating understanding of the required readings and video lectures, and positive contributions on Piazza, see below (worth 10%)
  • A final open-book online exam (worth 25%)


ZFU Certification and Online Dispute Resolution

ZFU Certification

The Mannheim Master of Applied Data Science & Measurement program is certified according to the regulations of the ZFU (Staatliche Zentralstelle für Fernunterricht).


Online Dispute Resolution

Online dispute resolution according to Art. 14 Sect. 1 ODR-VO: The European Commission provides a platform for online dispute resolution (ODR). You can find more information under


Located in the heart of the German and European economy, Mannheim Business School (MBS), the umbrella organization for management education at the University of Mannheim, is considered to be one of the leading institutions of its kind in Germany and is continuously ranked as Germany’s #1.