Home IB Maths Exam Practice Questions

AI SL Exam Practice Questions

Exam-style questions with full worked solutions and mark schemes for Applications & Interpretation Standard Level.

19 sets 5 topics P1 + P2 GDC-friendly questions included
Jump to: 📘 Number & Algebra 📗 Functions 📐 Geometry & Trig 📊 Stats & Prob ∫ Calculus
1

Topic 1

Number & Algebra

Number skills, sequences, series, and financial mathematics

Core Number Skills

Scientific notation, index laws, logarithm basics, approximation, upper and lower bounds, percentage error, accuracy and estimation, and solving equations with a GDC.

Sequences and Series

Sequence and series notation, sigma notation, arithmetic sequences and series, geometric sequences and series, and real-world applications.

Financial Mathematics

Compound growth and depreciation, loan amortisation, and annuities.

2

Topic 2

Functions

Linear, quadratic, exponential, sinusoidal, and piecewise models

Linear Graphs

Straight-line equations and relationships between parallel and perpendicular lines.

More Functions and Their Graphs

Function notation and mappings, inverse functions, key graph features, intersections of graphs, and quadratic, cubic, exponential, and sinusoidal functions.

Function Modelling

Linear and piecewise models, quadratic and cubic models, exponential models, direct and inverse variation, sinusoidal models, and strategies for selecting and developing suitable models.

3

Topic 3

Geometry & Trigonometry

Coordinate geometry, 3D geometry, trigonometry, and Voronoi diagrams

Essential Geometry

Coordinate geometry, perpendicular bisectors, arcs, and sectors.

Three-Dimensional Geometry

Coordinates in three dimensions, volume, and surface area.

Trigonometry

Pythagoras’ theorem, right-angled trigonometry, the sine rule, the cosine rule, triangle area, elevation and depression angles, bearings, and geometric constructions.

Voronoi Diagrams

Constructing and interpreting Voronoi diagrams and applying them to optimisation problems, including the toxic-waste-site problem.

4

Topic 4

Statistics & Probability

Data, regression, probability, distributions, and hypothesis testing

Statistical Essentials

Sampling and data collection, measures of centre and spread, frequency tables, data transformations, outliers, box plots, cumulative frequency graphs, histograms, and data interpretation.

Correlation and Regression

Scatter plots, correlation, Pearson’s correlation coefficient, Spearman’s rank correlation coefficient, comparison of correlation measures, and linear regression.

Probability Basics

Probability rules, event types, independent and mutually exclusive events, conditional probability, Venn diagrams, and tree diagrams.

Probability Distributions

Discrete probability distributions and expected values.

Binomial Distributions

The binomial distribution and the calculation of binomial probabilities.

Normal Distributions

The normal distribution and related probability calculations.

Hypothesis Testing

Principles of hypothesis testing, chi-squared tests for independence, goodness-of-fit tests, and the t-test.

5

Topic 5

Calculus

Differentiation, integration, and applications

Differentiation

The derivative concept, differentiating powers of x, gradients, tangents and normals, increasing and decreasing behaviour, local maxima and minima, and applications of differentiation in modelling.

Integration

Numerical integration using the trapezoidal rule, the basic principles of integration, and integrating powers of x.

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