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Table 2.

Linear regressions predicting Log W from Tsimane’ education level for the computer task (highly significant) followed by the card task (nonsignificant).

Residuals:
Min	1Q	Median	3Q	Max
−1.1209	−0.4343	−0.1016	0.3188	2.5396

Coefficients:
	Estimate	SE	t value	Pr(>\| t \|)
(Intercept)	−1.08663	0.07125	−15.251	<2e–16 ***
Education	−0.07422	0.01446	−5.134	9.39e–07 *

Residuals:
Min	1Q	Median	3Q	Max
−0.75909	−0.20395	0.02276	0.23466	0.63624

Coefficients:
	Estimate	SE	t value	Pr(>\| t \|)
(Intercept)	−1.417943	0.034819	−40.723	<2e–16 ***
Education	−0.010884	0.007065	−1.541	0.126

Residuals:
Min	1Q	Median	3Q	Max
−1.1209	−0.4343	−0.1016	0.3188	2.5396

Coefficients:
	Estimate	SE	t value	Pr(>\| t \|)
(Intercept)	−1.08663	0.07125	−15.251	<2e–16 ***
Education	−0.07422	0.01446	−5.134	9.39e–07 *

Residuals:
Min	1Q	Median	3Q	Max
−0.75909	−0.20395	0.02276	0.23466	0.63624

Coefficients:
	Estimate	SE	t value	Pr(>\| t \|)
(Intercept)	−1.417943	0.034819	−40.723	<2e–16 ***
Education	−0.010884	0.007065	−1.541	0.126

Note: lm(formula = W_value_lg ∼ Education, data = just_comp) ^†p < .1. *p < .05. **p < .01. ***p < .001.

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