You can see a conceptual style as the weighting over particular kinds of mental motion.
Recombination of weightings over mental motions creates a huge space of possible styles, but in reality it can be compressed into a few archetypes (convergent due to both mimesis and targeting similar goals)
Every major statistical concept can be seen as a tendency in conceptual style. Preferring linear vs. nonlinear models. Normal vs. power law distributions. Maximizing thought’s expected value vs. variance vs. skewness vs. kurtosis. Noticing overfitting (usually due to insufficient data) and correcting. Noticing a dearth of data and gathering more. Being well calabrated about confidence (vs. not). And on and on.
- Associative vs. Causal thinking
- Empiricism vs. Rationalism
- What empirically works vs. what should work, or what is consistent
- Narrative vs. Conceptual / Analytic / Statistical
- Critical / Skeptical vs. Application / Building on / Recombination (Yes and)
- Re-framing as a constructive version of the skeptical / critical mindset, which questions and replaces assumptions
- Working in the same direction with different assumptions, hopefully maintaining shared purpose
- Ontology / Paradigm Questioning (There’s an interconnected memeplex of assumptions)
- Breakdown of Categories (seeing their brokenness, oneness, or decomposition)
- Adding Complexity (distinctions, conditionals, decomposing) vs. Compressing to Simplicity (unifying, abstracting, synthesizing)