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: "Frequentist Significance Assessment"
Split Justification: This dichotomy separates the two core objectives of frequentist significance assessment: determining the statistical likelihood of observed data given the null hypothesis (typically via p-values) and estimating the size and uncertainty of the observed effect (typically via effect sizes and confidence intervals). These represent distinct but complementary analytical goals within a comprehensive frequentist interpretation.
11
From: "Quantifying Effect Magnitude and Precision"
Split Justification: This dichotomy directly separates the quantification of an effect's inherent strength or size from the quantification of the uncertainty or reliability associated with that size estimate. Measures of effect magnitude provide a point estimate or direct indicator of the effect's strength, while measures of estimation precision (e.g., confidence intervals, standard errors) describe the variability or range of plausible values for that magnitude, addressing the two core components of the parent concept distinctly and comprehensively.
12
From: "Measures of Estimation Precision"
Split Justification: This dichotomy separates measures of estimation precision into those that are expressed as a single numerical value (e.g., standard error, variance of the estimator) and those that are expressed as a range or interval (e.g., confidence intervals, margin of error). These two categories represent distinct and mutually exclusive approaches to quantifying and communicating the uncertainty and precision of an estimate, comprehensively covering the ways precision is typically measured.
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Topic: "Single-Value Measures of Precision" (W5743)