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Discrete probability distributionsEdexcel A-Level Maths: Revision notes

Section 1

Discrete random variables

A discrete random variable XX takes separate values xx, each with a probability P(X=x)P(X=x). A probability distribution lists these in a table or gives a formula. Two rules always hold: every P(X=x)P(X=x) lies between 00 and 11, and ∑P(X=x)=1.\sum P(X=x)=1. Because the values are mutually exclusive, the probability of several values is found by adding: P(X≥3)=P(X=3)+P(X=4)P(X\ge3)=P(X=3)+P(X=4). Example: P(X=x)=kxP(X=x)=kx for x=1,2,3,4x=1,2,3,4 gives 10k=110k=1, k=110k=\frac1{10} and P(X≥3)=0.7P(X\ge3)=0.7. (Calculating the mean and variance is not needed here.)

Key termsdiscrete random variableprobability distribution
Exam tip

If a distribution has an unknown constant, form an equation by setting the sum of all the probabilities to 11 first.

Section 2

Finding unknown constants

Set the sum of probabilities equal to 11 and solve. Example: P(Y=0)=0.15P(Y=0)=0.15, P(Y=1)=aP(Y=1)=a, P(Y=2)=2aP(Y=2)=2a, P(Y=3)=a+0.05P(Y=3)=a+0.05. Then 0.2+4a=10.2+4a=1, so a=0.2a=0.2 and the distribution is 0.15, 0.2, 0.4, 0.250.15,\ 0.2,\ 0.4,\ 0.25. Check that every value is between 00 and 11 and that they total 11. A solution giving a negative probability must be rejected.

Key termsconstant
Common mistake

Using P(X=x)=kxP(X=x)=kx and summing only some of the values, or treating the values as equally likely when the formula depends on xx.

Section 3

The discrete uniform distribution

A discrete uniform distribution has nn values, all equally likely, so P(X=x)=1nP(X=x)=\frac1n for each. Examples: a fair die (n=6n=6) or a fair eight-sided die, with P(X=x)=18P(X=x)=\frac18. Probabilities of events are then counted: P(X>5)=38P(X>5)=\frac38 for the eight-sided die, and P(X prime)=48=12P(X\text{ prime})=\frac48=\frac12. To identify one, check that all the values have the same probability. The total of two spins is not uniform, because some totals can be made in more ways than others.

Key termsdiscrete uniform distribution

Section 4

Two independent observations

If two values of XX are observed independently, then P(X1=a and X2=b)=P(X=a)P(X=b)P(X_1=a\text{ and }X_2=b)=P(X=a)P(X=b). To find the probability of a total, list every pair that gives it and add the products. With P(X=x)=0.1xP(X=x)=0.1x: a total of 33 needs (1,2)(1,2) or (2,1)(2,1), so 2×0.1×0.2=0.042\times0.1\times0.2=0.04. For two rolls of a fair eight-sided die, P(first>second)=12(1−18)=716P(\text{first}>\text{second})=\frac12\left(1-\frac18\right)=\frac7{16} by symmetry. Remember to count both orders when the values are different.

Key termsindependent observations
Common mistake

Counting only (1,2)(1,2) and forgetting (2,1)(2,1), which halves the answer.

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Exam questions on Discrete probability distributions

  1. The discrete random variable XX has probability distribution P(X=x)=kxP(X=x)=kx for x=1,2,3,4x=1,2,3,4, where kk is a constant.
    Two independent values of XX are observed. Find the probability that their sum is 3.2 marks
  2. A fair eight-sided die has faces numbered 1 to 8. The random variable XX is the score when the die is rolled once.
    The die is rolled twice. Find the probability that the first score is greater than the second.2 marks
  3. The discrete random variable YY takes the values 0, 1, 2 and 3, with P(Y=0)=0.15P(Y=0)=0.15, P(Y=1)=aP(Y=1)=a, P(Y=2)=2aP(Y=2)=2a and P(Y=3)=a+0.05P(Y=3)=a+0.05.
    Find the value of aa and hence P(Y≥2)P(Y\ge2).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).