last update: January 6, 2017        [HOME]

DBB150: Stats for Dummies


Prof. Dr. M. Rauterberg, Full Professor
Industrial Design, Designed Intelligence, Eindhoven University of Technology



Lectures (2 hours/week), exercises (2 hours/week) and homework assignments (4 hours/week); in total 8 lecture weeks + 2 weeks examination/re-examination.


This introductory course provides an overview over research based on empirical data and what we can learn from them. The art and science of learning from data helps students become statistically literate by encouraging them to ask and answer interesting statistical questions. It takes the ideas that have turned statistics into a central science in modern life and makes them accessible and engaging to students without compromising necessary rigor. The course has been designed for conciseness and clarity to keep students focused on the main concepts. The data-rich examples that feature intriguing design-interest topics now include topic labels to indicate which statistical topic is being applied. Clear learning objectives for each part make it easy to plan homework. Incorporates simulations in addition to the mathematical formulas enables the student to play with the data.

Learning Objectives

  • The art and science of learning from data.
  • Setting up empirical data gathering.
  • Step by step guide for research methodology.
  • Different scales for measuring.
  • Simple descriptive and inferential statistics.


Previous Knowledge

No specific pre-knowledge beyond basic math from highschool is required.


This introductory course provide first steps for planning an emprical data gathering study, how to measure concepts, and how to analyse the gathered data set according the specified research question(s).

Course work

The feedback for this course will be determined by the work done on the set of deliverables (Dx; see below). Each deliverable (Dx) will cover a number of steps.

Deliverables [Dx] Date due

For each 2-week block a report (min. 2 A4 pages) about the idea of the reserch question, measurements, data gathering method, and statistical analysis.

end of each block

D5: A text with reflections about the whole course (min. 1 A4 page)

end of week 8

Course schedule



Background material

week-1 & 2:

intro lecture: what is hard core science

Teacher: Rauterberg
obligatory material:

optional material:
Theory Building in Applied Disciplines

research methodology: step by step

Teacher: Rauterberg
obligatory material:

optional material:
Research Methodology
week-4: descriptive statistics

Teacher: Rauterberg
obligatory material:

optional material:
Art and Science of Data
week-5: population, sample, and inference

Teacher: Rauterberg
obligatory material:

optional material:
Art and Science of Data
week-6: test design, effect size, and test power

Teacher: Rauterberg
obligatory material:

optional material:
Essential Guide to Effect Sizes



alpha inflation and other important aspects

Teacher: Rauterberg

obligatory material:

optional material:
SPSS Demystified



Based on the reports each student will be evaluated individually.

obligatory material:
list of references

Feedback to Student

Students will be working in small teams; however, each student will be individually graded based on the quality of his/her written reports/documents and the presentations.

Feedback will be determined based on the innovation and rigour with which the work is done, and any initiative to ensure good quality of work. [RUBRIC]