Menyajikan simulasi menggunakan R untuk mempelajari pengaruh ukuran sampel, variabilitas data (standar deviasi), dan pengetahuan tentang standar deviasi populasi terhadap lebar interval kepercayaan 95%. Hasil simulasi menunjukkan bahwa ukuran sampel yang lebih besar menghasilkan interval kepercayaan yang lebih sempit, sedangkan variabilitas data yang lebih tinggi menghasilkan interval yang lebih lebar. Selain itu, penggunaan distribusi t ketika standar deviasi populasi tidak diketahui menghasilkan interval kepercayaan yang sedikit lebih luas dibandingkan distribusi normal.

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The Comprehensive Math Anxiety Assessment Scale (CMAAS) represents a paradigm shift in psychological measurement, moving beyond traditional symptom-focused approaches to target the specific neurobiological, cognitive, and behavioral mechanisms underlying mathematics anxiety. This 56-item multidimensional instrument assesses math anxiety across seven theoretically grounded domains—cognitive worry, affective distress, physiological arousal, behavioral patterns, value beliefs, self-efficacy, and social-cultural processes—each comprising four distinct facets for a total of 28 granular mechanisms. The scale was developed using a cutting-edge AI-assisted methodology leveraging the AIGENIE R package interfaced with local large language models via Ollama. Through carefully engineered prompts incorporating mechanism definitions, adaptive/maladaptive examples, and key linguistic markers, we generated items that maintain theoretical fidelity while using accessible, first-person language appropriate for adolescents and adults.