ATARMAxxing · Mathematical Methods
SACE Mathematical Methods Practice Exams with Worked Solutions
20 full-length papers · worked solutions for every question
The 20 practice exams inside the SACE Mathematical Methods Mastery Pack, each set out like the real paper with a separate worked-solution guide. Open any paper to see what it covers.
- routine derivatives with chain, product and quotient rules (1.2)
- normal distribution probabilities and inverse-normal values (5.2)
- upper and lower rectangle estimates of area (3.2)
- tangent to an exponential curve solved with ln (4.1)
- confidence interval for a population proportion (6.3)
- derivative of x^n from first principles (1.1)
- binomial probabilities and mean np (2.3)
- fundamental theorem of calculus for exact area (3.3)
- graph of y = ln(x) and its transformations (4.2)
- sampling distribution of the sample mean (5.3)
- second derivative, concavity and points of inflection (1.5)
- expected value and standard deviation of a discrete random variable (2.1)
- area between two curves (3.2)
- integral of f'(x)/f(x) (4.3)
- confidence interval for a population mean (6.1)
- derivatives of sine and cosine and periodic models (1.4)
- Bernoulli distribution parameters (2.2)
- integrating a rate of change to find total change (3.4)
- solving exponential equations with logarithm laws (4.1)
- central limit theorem and sample sums (5.3)
- optimisation of a modelled function using f' and f'' (1.5)
- binomial conditions and cumulative probabilities (2.3)
- indefinite integrals with an initial condition (3.1)
- derivative of ln(f(x)) and tangent lines (4.3)
- sample proportion p-hat and its standard deviation (6.2)
- tangent and normal equations for e^f(x) (1.3)
- probability density functions and their mean (5.1)
- displacement and distance from a velocity function (3.4)
- logarithmic model of growth and its rate of change (4.3)
- interpreting a confidence level and a claim (6.1)
- instantaneous velocity and acceleration from displacement (1.1)
- normal distribution: finding sigma from a known probability (5.2)
- definite integrals and signed area below the x-axis (3.2)
- asymptotes and intercepts of k ln(b(x - c)) (4.2)
- width of a confidence interval and sample size (6.3)
- product and quotient rule proofs of a given derivative (1.2)
- probability bar charts and uniform distributions (2.1)
- area under a curve by the fundamental theorem (3.3)
- exact solutions of e^(kx) = c (4.1)
- sampling distribution of the sample sum (5.3)
- sign diagrams and stationary points of a cubic (1.5)
- binomial mean and standard deviation in context (2.3)
- families of curves sharing a derivative (3.1)
- derivative of ln(x) at a point and tangent line (4.3)
- confidence interval for a proportion from survey data (6.3)
- chain rule with trigonometric compositions (1.4)
- z-scores and the standard normal distribution (5.2)
- area between a curve and a line (3.2)
- laws of natural logarithms in simplification (4.1)
- confidence interval for a mean with known sigma (6.1)
- derivative of e^(f(x)) and maxima of an exponential model (1.3)
- expected value as a long-run mean (2.1)
- total distance travelled from a velocity graph (3.4)
- transformations of ln(x) and domain (4.2)
- central limit theorem justification for approximate normality (5.3)
- average versus instantaneous rate of change (1.1)
- Bernoulli mean and standard deviation (2.2)
- estimating area with rectangles and explaining under- or over-estimation (3.2)
- integral of 1/(ax + b) forms (4.3)
- normal approximation of the sample proportion (6.2)
- quotient rule and the derivative of tan (1.4)
- inverse-normal calculations for cut-off scores (5.2)
- fundamental theorem of calculus with an exact irrational answer (3.3)
- exponential decay half-life solved with ln (4.1)
- interpreting whether a confidence interval supports a claim (6.1)
- nature of stationary points via the second derivative test (1.5)
- binomial probability of at least k successes (2.3)
- integration of linear-argument trigonometric functions (3.1)
- gradient of a logarithmic curve and its normal (4.3)
- effect of confidence level on interval width (6.3)
- first principles derivative of a rational power (1.1)
- valid probability density functions and P(a < X < b) (5.1)
- area under a rate-of-change graph as change in quantity (3.4)
- graph sketching of ln transformations on given axes (4.2)
- sample size needed for a required margin of error (6.3)
- chain rule with e^x inside a power (1.3)
- standard deviation of a discrete random variable (2.1)
- area of a region partly below the x-axis (3.2)
- solving simultaneous exponential equations with logarithms (4.1)
- mean and standard deviation of the sample mean (5.3)
- derivatives of trigonometric models and maximum rates (1.4)
- binomial distribution shape for large n (2.3)
- velocity from acceleration with an initial condition (3.4)
- integral of f'(x)/f(x) with domain restriction (4.3)
- confidence interval for a population mean and its interpretation (6.1)
- points of inflection: stationary and non-stationary (1.5)
- normal distribution proportions and percentiles (5.2)
- upper and lower sums with a stated number of rectangles (3.2)
- logarithm laws to rewrite and differentiate (4.3)
- confidence interval for a proportion and a claimed value (6.3)
- equation of a normal to a polynomial curve (1.1)
- Bernoulli versus binomial random variables (2.2)
- exact area via the fundamental theorem of calculus (3.3)
- asymptotic behaviour of exponential and logarithmic graphs (4.2)
- sampling distribution probabilities using sigma/sqrt(n) (5.3)
- product rule with exponential and trigonometric factors (1.2)
- mean of a continuous random variable by integration (5.1)
- integration to find displacement from velocity (3.4)
- exponential equation solved exactly with ln (4.1)
- interpreting a 95% confidence interval for a proportion (6.2)
Included in the SACE Mathematical Methods Mastery Pack
20 full-length practice exams with worked solutions, 20 revision notes, 64 practice questions and 200 flashcards.
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