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Probability density functionsAQA A-Level Further Maths: Revision notes

Section 1

Discrete and continuous random variables

A discrete random variable takes separate values (for example the score on a die), and each value has a probability P(X=x)P(X=x). A continuous random variable can take any value in an interval (for example a time or a mass), so we cannot list the values. Instead a continuous random variable is described by a probability density function (pdf) f(x)f(x). Probability is the area under the curve, not the height. Because a single value has no width, P(X=a)=0P(X=a)=0 for every aa, and therefore P(X<a)=P(X≤a)P(X<a)=P(X\le a).

Key termsdiscretecontinuousprobability density function
Common mistake

Reading f(a)f(a) as P(X=a)P(X=a). The value f(a)f(a) is a density and can even exceed 1; only areas are probabilities.

Section 2

What makes a valid pdf

A function ff is a pdf if both conditions hold:

  1. f(x)≥0f(x)\ge0 for all xx;
  2. the total area is 1: ∫−∞∞f(x) dx=1\int_{-\infty}^{\infty}f(x)\,dx=1. A pdf is usually given in pieces and is 00 outside the stated range, so only integrate over the range where ff is non-zero. If ff contains an unknown constant kk, integrate over the range, set the result equal to 1 and solve. For f(x)=kx2f(x)=kx^2 on [0,3][0,3]: ∫03kx2 dx=9k=1\int_0^3kx^2\,dx=9k=1, so k=19k=\frac19.
Key termstotal area

Section 3

Probabilities for an interval

The probability that XX lies between aa and bb is the area under ff between them: P(a<X<b)=∫abf(x) dx.P(a<X<b)=\int_a^bf(x)\,dx. Since P(X=a)=0P(X=a)=0, it makes no difference whether the inequalities are strict. For a tail, either integrate to the end of the range or use P(X>a)=1−P(X<a)P(X>a)=1-P(X<a). Example: f(x)=x29f(x)=\frac{x^2}{9} on [0,3][0,3] gives P(1<X<2)=[x327]12=8−127=727P(1<X<2)=\left[\frac{x^3}{27}\right]_1^2=\frac{8-1}{27}=\frac{7}{27}. When ff is defined in pieces, split the integral at the point where the formula changes.

Key termsinterval probability
Exam tip

If the range of integration crosses a change in the formula for ff, write two integrals and add them.

Section 4

Median and quartiles

The median mm is the value with half the probability below it: ∫−∞mf(x) dx=12.\int_{-\infty}^{m}f(x)\,dx=\frac12. The lower quartile Q1Q_1 satisfies ∫−∞Q1f(x) dx=14\int_{-\infty}^{Q_1}f(x)\,dx=\frac14 and the upper quartile Q3Q_3 satisfies ∫−∞Q3f(x) dx=34\int_{-\infty}^{Q_3}f(x)\,dx=\frac34. The interquartile range is Q3−Q1Q_3-Q_1. Integrate from the lower end of the range (since f=0f=0 below it), set the area equal to 12\frac12, 14\frac14 or 34\frac34 and solve. Reject any root outside the range of XX.

Key termsmedianlower quartileupper quartile
Common mistake

Giving a root that lies outside the range of XX. For a quadratic in mm, check each root against the stated limits.

Section 5

Worked example

f(x)=x18f(x)=\frac{x}{18} for 0≤x≤60\le x\le6, and 00 otherwise. Check: ∫06x18 dx=[x236]06=1\int_0^6\frac{x}{18}\,dx=\left[\frac{x^2}{36}\right]_0^6=1. P(X<3)=936=14P(X<3)=\frac{9}{36}=\frac14, and P(X=4)=0P(X=4)=0. Median: m236=12\frac{m^2}{36}=\frac12, so m2=18m^2=18 and m=32≈4.24m=3\sqrt2\approx4.24. Lower quartile: q236=14\frac{q^2}{36}=\frac14, so q=3q=3.

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Exam questions on Probability density functions

  1. The continuous random variable XX has probability density function f(x)=kx2f(x)=kx^2 for 0≤x≤30\le x\le3, and f(x)=0f(x)=0 otherwise, where kk is a constant.
    Find P(1<X<2)P(1<X<2).2 marks
  2. The continuous random variable XX has probability density function f(x)=x18f(x)=\frac{x}{18} for 0≤x≤60\le x\le6, and f(x)=0f(x)=0 otherwise.
    Find the median of XX.2 marks
  3. The continuous random variable XX has probability density function f(x)=kx(3−x)f(x)=kx(3-x) for 0≤x≤30\le x\le3, and f(x)=0f(x)=0 otherwise, where kk is a constant.
    Show that k=29k=\frac29.3 marks
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Written by the Exaim team, led by Shaun Daswani (Head of Upper Secondary, Improve ME Institute; MSc Financial Mathematics, Imperial College London; BSc, UCL) and Jason Daswani (operational lead, Improve ME Institute; LSE).