- pvalue = probability (in the null hypothesis distribution) to be observed as a value equal to or more extreme than the value observed
- Derive CDF -> find 0 regions = extremes
- Integrate from 0 regions towards region of increasing integral value.
- Once sum of all integrations is alpha, stop. Integrated area is a critical region
- Computation for x: integrate until the first integral boundary hits x. pvalue = sum of integrals
- Tabulation: for each desired pvalue compute boundaries (4 values) where critical region starts.
- pvalue(x): need to do the integration OR function table (\forall zscores: P(zscore) > 0).
- In our case 4 extremes, integrate:
- -\inf towards 0
- +\inf towards 0
- 0 towards +\inf
- 0 towards -\inf
- 10000 samples, pvalue = 0 -> 1/10000.
- absolutize -> we have a new distribution -> 2x more datapoints, 2 tails.