Review of Statistical Concepts

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Review of Statistical Concepts - Course Details

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

Single Course Price:

1,200.00 EUR (tax exempt)



Brian Kim, PhD (University of Maryland)

Video lecture:

Brian Kim, PhD (University of Maryland)


Course Dates

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This course is part of the Mannheim Data Science Certificate: Introduction to Survey and Data Science.

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
This course provides a brief overview of the basics of probability and statistics. Students will review basic probability concepts and probability distributions, the Central Limit Theorem and hypothesis testing, and linear and logistic regression. Throughout this course, students should develop and reinforce proper statistical intuition. This includes knowing how to identify a sample and a population and applying appropriate statistical methods such as hypothesis testing, as well being able to identify different types of data and using the proper methods for each type of data. By the end of the course, students should have a strong foundation in statistics with which they can start their graduate coursework.

No Prerequisites.

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

  • understand sample and population and know how to apply statistical methods appropriately
  • be able to apply basic probability
  • know basic probability distributions and how to apply them
  • perform hypothesis tests and construct confidence intervals
  • understand regression analysis, including multiple regression and logistic regression

Course Composition
This is a 6 ECTS course that runs for 12 weeks. The content of the course is broken down into 11 units:

  1. Introduction
  2. Descriptive Statistics
  3. Probability
  4. The Normal Distribution and Z-Scores
  5. Other Probability Distributions
  6. Confidence Intervals
  7. Central Limit Theorem and Hypothesis Testing
  8. Inference for Numerical Data
  9. Inference for Categorial Data
  10. Linear Regression
  11. Regression Assumptions, Multiple- and Logistic Regression

Learning and Teaching Methods
In this course, you are responsible for watching video-recorded lectures and reading the required literature for each unit prior to participating in 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.

Grading will be based on:

  • 11 homework assignments (worth 60% total)
  • Participation in online meetings and submission of questions demonstrating understanding of readings (worth 10%)
  • Online Final Exam (worth 30%)


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.