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The cumulative distribution function — 9231 FPS

Integrate on the correct branch and keep a cumulative distribution continuous. Normalise a density and compute probabilities and moments by integration.

Notes and key methods

Normalise a piecewise density by adding its separate integrals. The cumulative distribution \(F(x)=P(X\le x)\) must include all area to the left, including completed earlier pieces.

For an absolutely continuous variable, F is continuous, nondecreasing, zero below the support and one above it. At a point where f changes formula, match the two CDF expressions rather than resetting the accumulated probability.

A density f is nonnegative and integrates to one over its support. Probabilities are areas: \(P(a<X<b)=\int_a^b f(x)\,dx\). A density may be larger than 1; a probability cannot.

Use \(E(X)=\int xf(x)\,dx\), \(E(X^2)=\int x^2f(x)\,dx\) and \(\operatorname{Var}(X)=E(X^2)-E(X)^2\). A median m solves \(\int_{-\infty}^m f(x)\,dx=1/2\).

Check the conditions

Three worked examples

Example 1 · Piecewise densities and cumulative functions

The density is \(f(x)=kx\ (0\le x\le 4),\quad f(x)=k(8-x)\ (4<x\le 8)\), and zero elsewhere.

Diagram for this worked example
Use the labelled scales alongside the numerical method.
  1. Find k.
  2. Find E(X).
  3. Find Var(X).
  4. Find P(X≤1).
Show the reasoning

(a)

\(k(4^2/2+4^2/2)=1\implies k=\frac{1}{16}\)

Answer: \(\frac{1}{16}\).

(b)

\(E(X)=4\) by symmetry about the centre of the support.

Answer: \(4\).

(c)

\(\int(x-E(X))^2f(x)\,dx=\frac{8}{3}\)

Answer: \(\frac{8}{3}\).

(d)

\(\int_0^1x/16\,dx=\frac{1}{32}\)

Answer: \(\frac{1}{32}\).

Example 2 · Continuous densities and moments

X has density \(f(x)=kx^{1}\) for \(0\le x\le 5\) and zero elsewhere.

Diagram for this worked example
Use the labelled scales alongside the numerical method.
  1. Find k.
  2. Find E(X).
  3. Find Var(X).
  4. Find the median of X.
Show the reasoning

(a)

\(k\frac{5^{2}}{2}=1\implies k=\frac{2}{25}\)

Answer: \(\frac{2}{25}\).

(b)

\(\int_0^L xf(x)\,dx=\frac{10}{3}\)

Answer: \(\frac{10}{3}\).

(c)

\(E(X^2)-E(X)^2=\frac{25}{18}\)

Answer: \(\frac{25}{18}\).

(d)

\((m/5)^{2}=1/2\implies m=52^{-1/2}\)

Answer: \(3.53553390593274\).

Example 3 · Piecewise densities and cumulative functions

The density is \(f(x)=kx\ (0\le x\le 6),\quad f(x)=k(12-x)\ (6<x\le 12)\), and zero elsewhere.

Diagram for this worked example
Use the labelled scales alongside the numerical method.
  1. Find k.
  2. Find E(X).
  3. Find Var(X).
  4. Find P(X≤1).
Show the reasoning

(a)

\(k(6^2/2+6^2/2)=1\implies k=\frac{1}{36}\)

Answer: \(\frac{1}{36}\).

(b)

\(E(X)=6\) by symmetry about the centre of the support.

Answer: \(6\).

(c)

\(\int(x-E(X))^2f(x)\,dx=6\)

Answer: \(6\).

(d)

\(\int_0^1x/36\,dx=\frac{1}{72}\)

Answer: \(\frac{1}{72}\).

Common mistakes

Practise with answer checking

Original exam-style problems

Write complete solutions before opening the worked solution. The marking guidance rewards reasoning as well as answers.

Examination practice · 2020–2026

Apply the method to recent source-labelled questions from this chapter.

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