Course – Data-analysis & Statistics

October 31, 2024 10.00 - 16.00 h

After this course attendees are able to:

  1. Explain the basic principles behind statistical modelling (Central Limit Theorem).
  2. Choose appropriate bivariate data-analysis techniques* (given a particular research question), correctly apply these techniques (by formulating statistical hypotheses, checking the statistical assumptions and deriving the test statistic) and interpret their results in meaningful ways.
  3. Estimate a multivariate regression model, check its assumptions (normality, linearity, homoscedasticity) and interpret its outcomes.

* The following data-analysis techniques will be treated: descriptive data analysis (mean, median, variance, standard deviation), univariate (one sample t-test, proportion test) and bivariate parametric tests (paired/independent samples t-test, ANOVA, Pearson correlation) and a non-parametric test (chi-square).

Course description
In this course attendees will actively work on solving concrete statistical problems in the domains of transport, infrastructure and logistics using various bivariate and multivariate data-analysis techniques. The course will treat the basic principles behind statistical modelling so that attendees really understand what the results of statistical tests mean.

Attendees have to apply several data-analysis techniques to their own data (or a given dataset) and report the results in a brief research report.

Day 1 –   Basic principles behind statistical modelling, descriptive statistics and bivariate data-analysis techniques (Maarten Kroesen)

Day 2 –   Multiple regression (Eric Molin)

Course material
Slides and online materials

The working method consists of oral lectures combined with (short) in-class assignments using SPSS. To this end, students should bring a laptop with SPSS installed on it.


Course leaders: Dr. Maarten Kroesen and Dr. Eric Molin

Dates: 24 & 31 October 2024

Time: 10.00 – 16.00h

Location: TU Delft – room t.b.a.

ECTS: 1 (class only) |  3 (class + passing assignment)

Participation: free for TRAIL/Beta/OML/ERIM members and PhD students of participating TRAIL faculties. Others please contact the TRAIL Office

Registration: please click here.

© 2020 Research School TRAIL