These notes do not include the introduction to RHARKing: changing or creating the hypothesis after seeing the results.P-hacking: researchers collect or select data or statistical analyses until nonsignificant results become significant.Selective reporting: only reporting significant results, and not reporting the non-significant results. Publication bias: only articles with significant effects are published. So the problem is: the literature is not representative for the population. What can we do to avoid these biases/to make ‘great results’ less important? --> Registered reports: when you use pre-registration it is on forehand clear what you’re going to do and what you’re interested in, in a manner that is verifiable by others. Four central aspects of the Registered Reports Model are:Researchers decide hypotheses, study procedures and main analyses before data collectionPart of the peer review process takes place before studies are conductedPassing this stage of review virtually guarantees publicationOriginal studies and high-value replications are welcomeMethods of pre-registration include:Sample (size)Design, variablesMeasuresExclusion criteriaAnalysis planHow does it work? Authors submit the STAGE 1 manuscript, stage 1 peer review takes place and if the reviews are positive, the journal offers in-principle acceptance (IPA) regardless of the study outcome. The advantages of Registered Reports:--> For the scientific community:Rigorous review of theory and methodsEliminates publication bias and reporting biasIncreases the reproducibility of science--> For scientistsKeeping track of what you did and whyPeer review when it is most helpfulPublication guaranteed regardless of the resultsCommon misconceptions:1. ‘Pre-registration prevents the exploration of your data/creativity’. This is not the case. It allows for exploratory science, it simply prevents reporting exploratory analyses as confirmatory...