In Maths AI, Topic 1 emphasises real-world applications of number and algebra: financial mathematics, approximation, error analysis, and algorithmic problem solving rather than abstract algebraic manipulation.
Significant figures, decimal places, percentage error = |vₐ − vₑ|/vₑ × 100%. Upper and lower bounds for measurements. Estimation strategies for real-world quantities — e.g., estimating the number of grains of rice in a jar using volume calculations.
Arithmetic sequences model linear growth (e.g., salary increments). Geometric sequences model exponential growth/decay (compound interest, depreciation). Compound interest: FV = PV(1 + r/n)ⁿᵗ. Annuities and loan amortisation using the GDC finance solver. Students must interpret amortisation schedules.
Choosing appropriate models: linear, exponential, power, logistic. Using technology to fit models to data (GDC regression). Testing model validity by comparing predicted vs actual values. Understanding limitations of models — extrapolation dangers, domain restrictions.
Maths AA emphasises algebraic proof, binomial theorem, and formal series manipulation. Maths AI emphasises practical applications: financial mathematics (loans, investments, amortisation), estimation, and algorithmic thinking. Both cover sequences and series, but the application focus is different — AA is theoretical, AI is applied.
Book a Trial + Diagnostic session. Get a personalized Learning Path with clear milestones, tutor match, and a plan recommendation — all within 24 hours.
Book Trial + Diagnostic →