1. One simple step to improve statistical inferences
  2. Priors for Bayesian estimation of visual object processing speed in humans
  3. Simple steps for more informative ERP figures
  4. Robust effect sizes for 2 independent groups
  5. the percentile bootstrap
  6. how to fix erroneous error bars for percent correct data
  7. How to chase ERP monsters hiding behind bars
  8. The Harrell-Davis quantile estimator
  9. the shift function: a powerful tool to compare two entire distributions
  10. How to quantify typical differences between distributions
  11. A few simple steps to improve the description of neuroscience group results
  12. Matlab code for the shift function: a powerful tool to compare two entire marginal distributions
  13. Problems with small sample sizes
  14. A clearer explanation of the shift function
  15. How to illustrate a 2×2 mixed ERP design
  16. How to compare dependent correlations
  17. Trimmed means
  18. Your alpha is probably not 0.05
  19. Your power is lower than you think
  20. Bias & bootstrap bias correction
  21. What can we learn from 10,000 experiments?
  22. Can someone tell if a person is alive or dead based on a photograph?
  23. Reaction times and other skewed distributions: problems with the mean and the median [part 1] [part 2] [part 3] [part 4]
  24. A quick review of Reader et al. EJN 2018
  25. Cohen’s d is biased
  26. Bayesian shift function
  27. A new shift function for dependent groups?
  28. Test-retest reliability assessment using graphical methods
  29. Small n correlations cannot be trusted
  30. Correlations in neuroscience: are small n, interaction fallacies, lack of illustrations and confidence intervals the norm?
  31. Small n correlations + p values = disaster
  32. Power estimation for correlation analyses
  33. Measurement precision estimation, an alternative to power analyses
  34. Illustration of continuous distributions using quantiles
  35. Cluster correction for multiple dependent comparisons