Linear models to project future population are most accurate when applied to which locations in...

Linear models project population assuming a constant rate of change, which is most accurate in areas with stable, predictable growth patterns. Option D (small, slow-growing regions) fits this, as these areas typically have steady trends without sudden shifts. The APA’sAICP Certification Exam Content Outline(2022), under “Research and Assessment Methods,” states, “Linear population models are most accurate in small, slow-growing regions where growth rates are stable.” Options A (rapidly growing metropolitan areas) and C (rapidly growing suburbs) have volatile growth, making linear models less accurate. Option B (older central cities) often faces decline or gentrification, disrupting linear trends. TheCPC Study Manual(2024) confirms, “Linear models work best in small, slow-growing regions with consistent growth patterns,” supporting option D.