Assessment and exam practice.

Try this with Mathematics Methods

1. Check the task format, time limit and permitted materials with your school.
2. Start with one timed section or task and record where you spent the most time.
3. Review errors before attempting another section. Separate missing knowledge from timing problems.

View Mathematics Methods resources on ATARMAXXING ↗

Practice paper focus areas

• Exam 1 — derivatives of e^x, sin x and cos x with the chain rule (3.1); definite integrals by the fundamental theorem (3.2); binomial probability by formula (3.3)
• Exam 2 — product and quotient rules (3.1); area between two curves (3.2); expected value and variance of a discrete random variable (3.3)
• Exam 3 — second derivative test and points of inflection (3.1); f(x) from f'(x) and an initial condition (3.2); Bernoulli mean and variance (3.3)
• Exam 4 — optimisation in context (3.1); displacement and position from velocity and acceleration (3.2); linear change of scale and origin for E(X) and Var(X) (3.3)
• Exam 5 — increments formula for small changes (3.1); rectangle sums to estimate area (3.2); cumulative binomial probabilities with technology (3.3)
• Exam 6 — derivative of Ae^(kx) in a growth model (3.1); signed areas and additivity of definite integrals (3.2); uniform discrete random variables (3.3)
• Exam 7 — curve sketching from f' and f'' (3.1); the signed area function F(x) and F'(x) = f(x) (3.2); binomial contexts and assumptions (3.3)
• Exam 8 — derivatives of x sin x and e^(-x) sin x (3.1); total change from a marginal rate (3.2); point estimates from relative frequencies (3.3)
• Exam 9 — acceleration as the second derivative of position (3.1); integrals of the form f(ax - b) (3.2); inverse binomial problems for n or p (3.3)
• Exam 10 — chain rule with composite trigonometric functions (3.1); area under a curve with exact values (3.2); standard deviation of a discrete random variable (3.3)
• Exam 11 — concavity and the second derivative (3.1); linearity of anti-differentiation (3.2); binomial mean np and variance np(1 - p) (3.3)
• Exam 12 — derivative of tan x by the quotient rule (3.1); families of curves with the same derivative (3.2); Bernoulli random variables in two-outcome contexts (3.3)
• Exam 13 — optimisation with a derived constraint (3.1); area between curves with intersection points (3.2); probability distribution tables (3.3)
• Exam 14 — derivative of e^x from the limit definition of e (3.1); definite integral as a limit of sums (3.2); expected value as a measure of location (3.3)
• Exam 15 — trigonometric derivatives in a practical model (3.1); position from acceleration with initial values (3.2); binomial probability of at least or at most (3.3)
• Exam 16 — second derivative and points of inflection on a sketch (3.1); integrals of e^x, sin x and cos x (3.2); effects of aX + b on mean and standard deviation (3.3)
• Exam 17 — product rule with exponential and trigonometric factors (3.1); fundamental theorem proof illustrated geometrically (3.2); modelling data with a discrete random variable (3.3)
• Exam 18 — increments formula and percentage change (3.1); total change from a rate of flow (3.2); non-uniform discrete random variables (3.3)
• Exam 19 — stationary points and their nature (3.1); area under a curve estimated with sums then exact (3.2); binomial modelling of a survey (3.3)
• Exam 20 — exponential decay model and its derivative (3.1); linear motion: displacement versus distance (3.2); Bernoulli trials and independence (3.3)