STPM Mathematics 954 study materials
STPM Mathematics 954 study resources

STPM Mathematics 954 key terms

STPM Mathematics 954 · Get comfortable with the vocabulary.

Function

A rule that assigns to each element of a domain exactly one element of a codomain. Written f: X → Y, where f(x) denotes the unique output for input x.

Related: Domain, Range, Composite Function
Domain

The complete set of input values for which a function is defined. For a rational function, values making the denominator zero are excluded from the domain.

Related: Function, Range, Asymptote
Range

The set of all actual output values a function produces as its input varies over the domain. It is a subset of the codomain.

Related: Function, Domain, Inverse Function
Composite Function

A function formed by applying one function to the result of another, written f∘g with (f∘g)(x) = f(g(x)). The domain of g must lie within the domain of f.

Related: Inverse Function, Function
Inverse Function

A function that reverses another, so f⁻¹(f(x)) = x for every x in the domain. It exists only when the original function is one-to-one.

Related: One-to-One Function, Composite Function, Range
One-to-One Function

A function where distinct inputs always give distinct outputs. Its graph passes the horizontal line test, and it has an inverse function.

Related: Inverse Function, Function
Polynomial

An expression of the form aₙxⁿ + ... + a₁x + a₀ with non-negative integer powers and real coefficients. Its degree is the highest power with a non-zero coefficient.

Related: Factor Theorem, Remainder Theorem, Partial Fractions
Factor Theorem

A polynomial P(x) has factor (x − a) exactly when P(a) = 0. Used to factorise polynomials and find their roots.

Related: Remainder Theorem, Polynomial
Remainder Theorem

When a polynomial P(x) is divided by (x − a), the remainder equals P(a). Dividing by (ax − b) gives remainder P(b/a).

Related: Factor Theorem, Polynomial
Partial Fractions

Decomposing a rational expression into a sum of simpler fractions with linear or quadratic denominators. Useful for integration and binomial expansion of rational functions.

Related: Polynomial, Integration by Substitution
Modulus Function

The function |x| giving the non-negative distance of x from zero: |x| = x for x ≥ 0 and |x| = −x for x < 0. Its graph is V-shaped.

Related: Inequality, Function
Inequality

A statement comparing two expressions using <, ≤, > or ≥. Solving it means finding all values satisfying the comparison, often expressed as an interval.

Related: Modulus Function, Domain
Exponential Function

A function of the form f(x) = aˣ with a > 0 and a ≠ 1. Its graph always passes through (0, 1) and has the x-axis as a horizontal asymptote.

Related: Logarithm, Asymptote
Logarithm

The inverse of an exponential: logₐ y = x means aˣ = y. Laws include log(xy) = log x + log y and log(xⁿ) = n log x.

Related: Exponential Function, Inverse Function
Asymptote

A line that a curve approaches ever more closely without necessarily meeting. Vertical asymptotes occur where a rational function's denominator is zero.

Related: Domain, Exponential Function
Limit

The value a function approaches as its input approaches a particular point. Written lim(x→a) f(x) = L; the function need not equal L at x = a.

Related: Continuity, Derivative
Continuity

A function is continuous at a point when the limit there exists, equals the function's value, and the function is defined. Informally, the graph has no break.

Related: Limit, Differentiability
Derivative

The instantaneous rate of change of a function, defined as the limit of a difference quotient. Geometrically it gives the gradient of the tangent to the curve.

Related: Limit, Chain Rule, Product Rule
Differentiability

A function is differentiable at a point when its derivative exists there. Differentiability implies continuity, but continuity does not guarantee differentiability.

Related: Derivative, Continuity
Chain Rule

A rule for differentiating composite functions: if y = f(u) and u = g(x), then dy/dx = (dy/du)(du/dx). Essential for functions such as sin(3x²).

Related: Derivative, Composite Function, Product Rule
Product Rule

A rule for differentiating a product: if y = uv then dy/dx = u(dv/dx) + v(du/dx), where u and v are functions of x.

Related: Quotient Rule, Chain Rule, Derivative
Quotient Rule

A rule for differentiating a quotient: if y = u/v then dy/dx = [v(du/dx) − u(dv/dx)]/v². Useful for rational functions of x.

Related: Product Rule, Derivative
Stationary Point

A point on a curve where the derivative equals zero. It may be a local maximum, local minimum, or point of inflection, classified using the second derivative.

Related: Second Derivative, Derivative
Second Derivative

The derivative of the derivative, written d²y/dx². It measures how the gradient changes and helps classify stationary points as maxima or minima.

Related: Stationary Point, Derivative
Integration by Substitution

A technique for evaluating integrals by changing the variable, reversing the chain rule. The limits must also be converted when the integral is definite.

Related: Definite Integral, Chain Rule, Partial Fractions
Definite Integral

The integral of a function between two limits, written ∫ₐᵇ f(x) dx. It represents the signed area between the curve and the x-axis.

Related: Integration by Substitution, Area Under a Curve
Area Under a Curve

The region between a curve y = f(x) and the x-axis from x = a to x = b, found by a definite integral. Regions below the axis count as negative.

Related: Definite Integral
Vector

A quantity with both magnitude and direction, often written as a column or in i, j, k components. It differs from a scalar, which has magnitude only.

Related: Scalar Product, Unit Vector, Position Vector
Position Vector

A vector giving the location of a point relative to a fixed origin, usually written OA for point A. Used to express lines and planes in vector form.

Related: Vector, Direction Vector
Unit Vector

A vector with magnitude exactly one, obtained by dividing a vector by its magnitude. The unit vectors along coordinate axes are i, j and k.

Related: Vector, Scalar Product
Scalar Product

The dot product of vectors a and b, defined as |a||b|cos θ, giving a scalar. It is zero when the vectors are perpendicular.

Related: Vector, Unit Vector, Direction Vector
Direction Vector

A vector parallel to a line indicating its orientation. A line through point A with direction d has equation r = a + t d, where t is a scalar parameter.

Related: Position Vector, Scalar Product, Vector
Random Variable

A variable whose value is a numerical outcome of a random experiment. It may be discrete, taking countable values, or continuous, taking any value in an interval.

Related: Probability Distribution, Expectation, Normal Distribution
Probability Distribution

A description of the possible values of a random variable together with their probabilities. For a discrete variable it is given by a probability function summing to one.

Related: Random Variable, Binomial Distribution, Normal Distribution
Expectation

The mean value of a random variable, written E(X). For a discrete variable it is the sum of each value multiplied by its probability.

Related: Variance, Random Variable
Variance

A measure of spread defined as Var(X) = E(X²) − [E(X)]². It is the average of the squared deviations from the mean; its square root is the standard deviation.

Related: Expectation, Normal Distribution, Standard Deviation
Binomial Distribution

The distribution of the number of successes in n independent trials, each with the same success probability p. Written X ~ B(n, p), with mean np and variance np(1 − p).

Related: Probability Distribution, Normal Distribution, Random Variable
Normal Distribution

A continuous, symmetric bell-shaped distribution defined by its mean μ and variance σ². Written X ~ N(μ, σ²); probabilities are found by standardising to Z.

Related: Standard Normal Distribution, Variance, Binomial Distribution
Standard Normal Distribution

The normal distribution with mean zero and variance one, denoted Z ~ N(0, 1). Any normal variable is converted using Z = (X − μ)/σ before using tables.

Related: Normal Distribution, Standard Deviation
Standard Deviation

The positive square root of the variance, expressed in the same units as the data. It measures the typical distance of observations from the mean.

Related: Variance, Standard Normal Distribution
Null Hypothesis

The statement assumed true at the start of a significance test, usually claiming no effect or no difference. Denoted H₀ and tested against an alternative hypothesis.

Related: Alternative Hypothesis, Significance Level, Test Statistic
Alternative Hypothesis

The statement accepted when sample evidence is strong enough to reject the null hypothesis. It may be one-tailed or two-tailed, denoted H₁.

Related: Null Hypothesis, Significance Level
Significance Level

The probability, chosen before testing, of rejecting a true null hypothesis, commonly 0.05 or 0.01. It defines the critical region of the test.

Related: Critical Region, Null Hypothesis, Type I Error
Test Statistic

A value calculated from sample data and compared with a critical value to decide on the null hypothesis. Examples include the sample mean standardised as a z-score.

Related: Critical Region, Null Hypothesis, Significance Level
Critical Region

The set of test statistic values that leads to rejecting the null hypothesis. Its total probability under the null hypothesis equals the significance level.

Related: Significance Level, Test Statistic, Type I Error
Type I Error

Rejecting a null hypothesis that is actually true. Its probability equals the significance level chosen for the test.

Related: Type II Error, Significance Level, Null Hypothesis
Type II Error

Failing to reject a null hypothesis that is actually false. Its probability is denoted β, and 1 − β is called the power of the test.

Related: Type I Error, Alternative Hypothesis
Confidence Interval

A range of values, calculated from a sample, that is likely to contain an unknown population parameter. The confidence level states the long-run proportion of such intervals that capture the parameter.

Related: Test Statistic, Standard Normal Distribution, Standard Deviation