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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:
Min1QMedian3QMax
−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:
Min1QMedian3QMax
−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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