1
From: "Human Potential & Development."
Split Justification: Development fundamentally involves both our inner landscape (**Internal World**) and our interaction with everything outside us (**External World**). (Ref: Subject-Object Distinction)..
2
From: "Internal World (The Self)"
Split Justification: The Internal World involves both mental processes (**Cognitive Sphere**) and physical experiences (**Somatic Sphere**). (Ref: Mind-Body Distinction)
3
From: "Cognitive Sphere"
Split Justification: Cognition operates via deliberate, logical steps (**Analytical Processing**) and faster, intuitive pattern-matching (**Intuitive/Associative Processing**). (Ref: Dual Process Theory)
4
From: "Analytical Processing"
Split Justification: Analytical thought engages distinct symbolic systems: abstract logic and mathematics (**Quantitative/Logical Reasoning**) versus structured language (**Linguistic/Verbal Reasoning**).
5
From: "Quantitative/Logical Reasoning"
Split Justification: Logical reasoning can be strictly formal following rules of inference (**Deductive Proof**) or drawing general conclusions from specific examples (**Inductive Reasoning Case Study**). (L5 Split)
6
From: "Inductive Reasoning Case Study"
Split Justification: Induction involves forming general rules (**Hypothesis Generation**) and testing their predictive power (**Hypothesis Testing**). (L6 Split)
7
From: "Hypothesis Testing"
Split Justification: Testing a hypothesis involves designing a fair test (**Designing a Simple Experiment**) and drawing conclusions from the outcome (**Interpreting Results**).
8
From: "Interpreting Results"
Split Justification: This dichotomy separates the objective, quantitative evaluation of the evidence from the hypothesis (Statistical Significance Assessment) from the more qualitative, integrative process of understanding the real-world implications, limitations, and broader significance of those findings (Contextual Meaning Derivation).
9
From: "Statistical Significance Assessment"
Split Justification: This dichotomy represents the two primary and distinct statistical paradigms used for conceptualizing, quantifying, and interpreting statistical significance, each employing unique methodological frameworks and metrics (e.g., p-values vs. Bayes factors).
10
From: "Bayesian Significance Assessment"
Split Justification: This dichotomy differentiates between Bayesian approaches that assess significance by directly comparing the posterior probability or evidence for competing hypotheses (e.g., using Bayes Factors) and those that assess significance by examining the credibility of specific parameter values within their posterior distribution (e.g., using credible intervals or Regions of Practical Equivalence, ROPEs).
11
From: "Bayesian Hypothesis Comparison for Significance"
Split Justification: Bayesian hypothesis comparison for significance fundamentally involves quantifying the relative evidence provided by the data (often via Bayes Factors) and integrating this evidence with prior beliefs to assess the updated posterior probability of each hypothesis. These represent distinct yet complementary aspects of determining significance.
12
From: "Assessment of Posterior Belief in Hypotheses"
Split Justification: This dichotomy separates the assessment of posterior belief into quantifying the absolute probability of individual hypotheses versus quantifying the relative strength of belief between hypotheses using odds ratios or Bayes factors. Both are distinct and fundamental approaches to assessing posterior belief within a Bayesian framework.
✓
Topic: "Comparative Posterior Belief (Odds and Bayes Factors)" (W7535)