Compute z-statistic (ZScoreStandard)

class cerebstats.stat_scores.zScore.ZScoreStandard(*args: Any, **kwargs: Any)

Compute t-statistic as the standardized statistic as

Definitions

Interpretation

sample_mean, \(\bar{x}\)

observation[“mean”]

null_value, \(\mu_0\)

model prediction

standard_deviation, sd

observation[“standard_deviation”]

z-statistic, z

z = \(\frac{\bar{x} - \mu_0}{sd}\)

Note: se = \(\frac{s}{\sqrt{n}}\), where n is the sample size and s is the standard deviation.

Use Case

x = ZScoreStandard.compute( observation, prediction )
score = ZScoreStandard(x)

Note: As part of the SciUnit framework this custom ZScoreStandard should have the following methods,

  • compute() (class method)

  • sort_key() (property)

  • __str__()

classmethod compute(observation, prediction)

Note:

  • observation (sample) is in dictionary form with keys mean and

  • standard_error whose value has magnitude and python quantity

  • the populations parameter is the predicted value