Are eye colour and handedness independent in a sampled population?
Approach · Survey a sample, build a contingency table, and apply a chi-squared test of independence with expected-frequency checks.
Math: Applications & Interpretation · IA research questions
Written and cross-checked by IB Diploma graduates: Alexander (41), Alejandro (40), Martina (40), Victoria (38), Martin (35), Maria (34)
· Checked against official IB guidance · Editorial policy
A strong Maths AI exploration is built on real data and a real-world decision. Statistics (regression, chi-squared, confidence intervals), modelling (exponential, trigonometric, numerical integration) and applied topics like graph theory and Voronoi diagrams all fit well — the point is to interpret the answer, not just compute it.
Scope: Gather your own data (survey, measurement, or a clean published dataset) with enough points for the technique to be valid. State assumptions and evaluate the model's fit. 12–20 pages.
Approach · Survey a sample, build a contingency table, and apply a chi-squared test of independence with expected-frequency checks.
Approach · Collect listing data, fit linear and non-linear regression models, report R², and give a confidence interval for the slope.
Approach · Log temperature over time, fit T = T_room + Ae^(−kt), and assess the fit with residual analysis.
Approach · Plot existing sites, construct a Voronoi diagram, and identify the largest under-served cell.
Approach · Model the road network as a weighted graph, apply Dijkstra / a nearest-neighbour TSP heuristic, and compare to the current route.
Approach · Fit h(t) = a sin(b(t − c)) + d to monthly data and test its predictions for the equinoxes and solstices.
Approach · Collect or use published score data, standardise, and run a goodness-of-fit test against the normal model.
Approach · Use the trapezium rule (or Simpson's rule) on cross-sectional areas from a contour map and give an uncertainty.
Approach · Survey a sample, compute the correlation coefficient, fit a regression line, and give a confidence interval for the gradient.
Approach · Fit a logistic curve to historical adoption figures and evaluate its short-term forecast against held-back data.
Approach · Simulate both repeatedly from a known population, compare the spread of the estimates, and relate it to standard error formulas.
Approach · Model the loan as an annuity, compute total interest for several terms and rates, and present the trade-off.
Primary-source references used to verify key assessment facts on this page. Last source check: September 22, 2026.
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