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 Generation"
Split Justification: Generating a hypothesis requires identifying a pattern (**Observing Correlations**) and formulating a testable explanation (**Stating a Falsifiable Claim**).
8
From: "Observing Correlations"
Split Justification: This dichotomy separates the process of identifying relationships based on numerical data and statistical analysis from the process of discerning patterns and connections within non-numerical, descriptive, or categorical information. Together, these two categories comprehensively cover the fundamental modes of observing correlations in any form of data or experience for hypothesis generation.
9
From: "Observing Quantitative Correlations"
Split Justification: This split categorizes the observation of quantitative correlations based on the number of variables involved in the relationship. A quantitative correlation fundamentally involves either two variables (bivariate) or more than two variables (multivariate), making these categories mutually exclusive and jointly exhaustive for any observed quantitative relationship.
10
From: "Observing Multivariate Quantitative Correlations"
Split Justification: This dichotomy distinguishes between correlations immediately apparent from raw data or simple direct calculations (e.g., a correlation matrix, direct scatterplot analysis) and those that are inferred or revealed through more complex statistical modeling of underlying, unobserved (latent) variables or mediating relationships.
11
From: "Observing Latent or Indirect Multivariate Quantitative Correlations"
Split Justification: This dichotomy separates the two primary ways correlations can be "latent or indirect". Child 1 focuses on situations where the variables themselves are unobserved constructs (latent variables), and the task is to infer these variables and observe their quantitative interrelationships. Child 2 focuses on situations where the quantitative relationships between variables (which may be observed or latent) are not direct, but instead operate through mediating or moderating pathways, thereby making the overall correlation indirect. This covers the two distinct challenges implied by "latent *or* indirect" in the parent node.
12
From: "Observing Correlations Among Latent Variables"
Split Justification: This dichotomy distinguishes between the discovery-oriented process of identifying patterns and relationships among latent variables without strong prior hypotheses (exploratory) and the hypothesis-testing process of evaluating pre-specified theoretical models of latent variable relationships (confirmatory). Together, these two approaches comprehensively cover the methodologies for observing correlations among latent variables.
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Topic: "Observing Confirmatory Correlations Among Latent Variables" (W6927)