Published data#

Published aggregate data used in the examples and tests.

These are the only human data shipped with the package; every value is taken from the source named and was checked against secondary reports.

  • CLINTON_GORE: Gallup poll, 6-7 September 1997 (Moore, 2002; analysed by Wang and Busemeyer, 2013): “Do you generally think [Bill Clinton / Al Gore] is honest and trustworthy?” Proportion yes: Clinton first 0.50, Gore first 0.68, Clinton second 0.57, Gore second 0.60.

Functions

proportions_to_counts

Turn proportions into binary counts.
proportions_to_counts(props, n)[source]#

Turn proportions into binary counts.

Used to fit multinomial models when only proportions and a sample size are known.

Parameters:

  • props (dict) – {condition: p}.

  • n (int) – Sample size per condition.

Returns:

dict – {condition: [round(n p), n - round(n p)]}.

Examples

>>> from quantum_mind.data import proportions_to_counts
>>> proportions_to_counts({'unknown': 0.36}, 98)['unknown'].tolist()
[35, 63]