1. The often used expression 'flat prior' for a low-informative prior is confusing (this thesis)
  2. In this data-flooded are there is still need for the advancement of "small data science" (this thesis)
  3. Presenting scientific concepts in a difficult way harms their scientific quality
  4. All scientific models are useful
  5. Good scientists make bad programmers
  6. A manuscripts' accompanying source code should undergo the same rigid review as the manuscript itself
  7. All members of society — not only Bayesians — should be aware of uncertainty in any form of data, information, knowledge and wisdom
  8. The urgency for behavioural change to solve the climate crisis transcends by far the urgency of behavioural change regarding the COVID-19 crisis

Propositions belonging to the thesis, entitled: Model-based Bayesian geostatistics for multi-scale mapping of soil and agronomic variables

Luc Steinbuch
Wageningen, 22 April 2021