… analysis was the best predictor of causal thinking across both studies, but statistical thinking
supported and informed spatial–temporal analysis: covariation … for causal analysis than …

… Variation and covariation became necessary in Thompson’s theory of quantitative … avoids
using the customary terms independent variable and dependent variable in any causal sense. …

… test the conceptual consistency of the covariation and mechanism principles in a more
structured manner. For instance, participants might be asked to evaluate various manifestations of …

… We could also rule out that the observed decrease in the P ( c → e| c ) ratings … ) we used
the generalized power PC model of singular causation judgments to provide a formal analysis …

… can override other cues to causality (including covariation evidence and temporal cues) and
… and C , suggesting that participants had used the principle of causal transitivity to combine …

… causal-induction principles that are a derivation of the control of variables strategy (schema)
we use. … share the same causal features should not differ in performance (hereafter, same …

… spatial–temporal analysis: covariation assessment potentially … widely important for causal
analysis than commonly assumed, … Covariation and temporal contiguity as principles of causal …

… and direct causal factors to the covariation between two … principle, a better approach would
be a trivariate analysis including initiation as a separate variable in the model (and code use …

… to cause such traits to covary in adaptively helpful ways. … generate trait covariation, we need
to use the principles of those … Darwinian principles that explain inter-species trait covariation …

… based on covariance/correlation for the analysis of multivariate metabolomics data [such as
principal component analysis or covariance simultaneous component analysis (Smilde et al. …