glossary.yml

alpha: |
  The threshold chosen in Neyman-Pearson hypothesis testing to distinguish test results that lead to the decision to reject the null hypothesis, or not, based on the desired upper bound of the Type 1 error rate. An alpha level of 5% is most commonly used, but other alpha levels can be used as long as they are determined and preregistered by the researcher before the data is analyzed.

p-value: |
  The probability of the observed data, or more extreme data, if the null hypothesis is true. The lower the p-value, the higher the test statistic, and less likely it is to observe the data if the null hypothesis is true.

effect size: |
  'quantitative reflection of the magnitude of some phenomenon that is used for the purpose of addressing a question of interest' (Kelley & Preacher, 2012)

power: |
  The probability of rejecting the null hypothesis when it is false, for a specific analysis, effect size, sample size, and criteria for significance.

SESOI: |
  Smallest Effect Size of Interest: the smallest effect that is theoretically or practically meaningful

  See [Equivalence Testing for Psychological Research](https://doi.org/10.1177/2515245918770963) for a tutorial on methods for choosing an SESOI.

html: |
  This is a paragraph with a [link](https://url.com).

  And another paragraph before a list:

  * Item 1
  * List 2