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NotesMath AA HLTopic 4.7
Unit 4 · Statistics & Probability · Topic 4.7

IB Math AA HL — Discrete random variables

Topic 4.7 of IB Mathematics: Analysis and Approaches covers Discrete random variables, which is part of Unit 4: Statistics & Probability. Students explore key concepts including Discrete random variables & probability distributions, Building probability distributions, Expected value, and more. A strong understanding of discrete random variables is essential for IB Math AA HL exams and builds the foundation for connected topics across the syllabus.

Higher Level students should use this topic hub as a map: start with the shared sub-topics, then follow the HL-only extensions and exam-skill links where this topic asks for deeper analysis.

Exam technique guidePractice questions

Key concepts in Discrete random variables

Topic 4.7: exam essentials

RememberMeaning
$\sum P(X=x)=1$All probabilities add to 1
$E(X)=\sum xP(X=x)$Multiply each value by its probability; add
Expected valueLong-run average
$E(\text{gain})=0$Fair game
Gain = prize − costMoney left after paying to play
$np$Expected number of occurrences
Independent trialsMultiply within each pair
Several possible pairsAdd their probabilities

Which method do I use? Missing chance: subtract the known chances from 1. Average score: multiply each score by its chance, then add. Fair game: average gain must be 0. How many losses: games × chance of losing. Two independent plays: list the pairs, multiply their chances, then add. Formula: put each allowed value into it.

Choose the right skill

Discrete random variables & probability distributions

Exam skillMethod
Missing probabilityKnown chances + missing chance = 1
Probability formulaSubstitute each allowed x

Building probability distributions

Exam skillMethod
Build a distributionList → group by X → count → divide

Expected value

Exam skillMethod
Expected valueMultiply each value by its chance, then add
InterpretAverage over many trials; may not occur in one trial

Fair games & expected money

Exam skillMethod
Fair gameAverage net gain = 0
Fair feeFee = average prize

Expected value in decisions

Exam skillMethod
Choose an optionCompare averages and risk; explain your choice
Outcome depends on xInclude −x for losing your current points

Repeated trials & expected outcomes

Exam skillMethod
Two independent trialsMultiply within pairs; add different pairs
Expected countNumber of trials × chance

Combined exam-style question

This original question combines building a distribution, expected gain, a fair fee, expected losses and two independent plays.

A game uses two fair coins. The prize is 0 dollars for no heads, 4 dollars for one head and 8 dollars for two heads. A player pays 3 dollars to play. (a) Find the probability distribution of the player’s net gain X. [3] (b) Find E(X) and interpret your answer. [2] (c) Find the entry fee that makes the game fair. [2] (d) The game is played 60 times. Find the expected number of losses. [2] (e) Two plays are independent. Find the probability that the total prize is 8 dollars. [3]

(a) What do you gain or lose?

Key Idea: X = prize − 3 dollars. A negative X means you lose money.
Coin resultPrizeX: prize − cost
TT: no heads0 dollars0 − 3 = −3 dollars
HT: one head4 dollars4 − 3 = 1 dollar
TH: one head4 dollars4 − 3 = 1 dollar
HH: two heads8 dollars8 − 3 = 5 dollars

4 equally likely results: each has probability 1/4. HT and TH both give X = 1, so add their chances: 1/4 + 1/4 = 1/2.

X: gain or lossResults giving this XProbability
−3 dollarsTT$1/4$
1 dollarHT or TH$1/2$
5 dollarsHH$1/4$

(b) Average gain

Find E(X) and explain what it means.

Step by step:

  1. (b) Multiply each net gain by its probability and add.

    E(X)=−3(14)+1(12)+5(14)=1E(X)=-3(\tfrac14)+1(\tfrac12)+5(\tfrac14)=1E(X)=−3(41​)+1(21​)+5(41​)=1
  2. Interpret: the player gains an average of 1 dollar per game in the long run.

Final answer:

Over many games, the player gains an average of 1 dollar per game.

(c) A fair entry fee

What should the player pay so the game is fair?

Step by step:

  1. The four equally likely results pay $0, $4, $4 and $8. Add the prizes and divide by 4.

    (0+4+4+8)÷4=4(0+4+4+8)\div4=4(0+4+4+8)÷4=4
  2. On average you receive $4. Pay $4 to leave no average gain or loss.

    4−4=04-4=04−4=0
Final answer:

Fair entry fee: $4.

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(d) Expected losses

Using the original 3-dollar entry fee, how many losses do we expect in 60 games?

Step by step:

  1. You lose money only with TT: you pay 3 dollars and win nothing. TT is 1 of the 4 equally likely results.

  2. The chance of losing is 1/4. Take one quarter of 60 games.

    60÷4=1560\div4=1560÷4=15
Final answer:

Expect 15 losses on average. A particular set of 60 games could have more or fewer.

(e) Total prize from two plays

Find the chance that the two prizes add to 8 dollars.

Step by step:

  1. There are three ways to make $8: $0 then $8, $4 then $4, or $8 then $0.

  2. For each pair, multiply the two chances. The plays are independent.

    (14)(14)=116,(12)(12)=14,(14)(14)=116(\tfrac14)(\tfrac14)=\tfrac1{16},\quad(\tfrac12)(\tfrac12)=\tfrac14,\quad(\tfrac14)(\tfrac14)=\tfrac1{16}(41​)(41​)=161​,(21​)(21​)=41​,(41​)(41​)=161​
  3. Add the chances of these three different ways.

    116+14+116=38=0.375\tfrac1{16}+\tfrac14+\tfrac1{16}=\tfrac38=0.375161​+41​+161​=83​=0.375
Final answer:

Probability = 3/8 = 0.375.

A prize is before the entry fee. A gain is after the fee. In part (e), the total is a prize total, so use prizes 0, 4 and 8.

IB-style question — find k so the probabilities sum to 1

A discrete random variable X has P(X = x) = kx for x = 2, 4, 6, 8. Find the value of k, then state P(X = 6).

Step by step:

  1. Add all four probabilities and set the total equal to 1.

    k(2+4+6+8)=20k=1k(2 + 4 + 6 + 8) = 20k = 1k(2+4+6+8)=20k=1
  2. Solve for k.

    k=120=0.05k = \tfrac{1}{20} = 0.05k=201​=0.05
  3. Substitute back to get the probability asked for.

    P(X=6)=6k=6(0.05)=0.3P(X = 6) = 6k = 6(0.05) = 0.3P(X=6)=6k=6(0.05)=0.3
Final answer:

k = 0.05; P(X = 6) = 0.3.

IB-style question — compute the expected value E(X)

The number of goals X a team scores in a match has this distribution: P(X = 0) = 0.2, P(X = 1) = 0.5, P(X = 2) = 0.2, P(X = 3) = 0.1. Find E(X), the expected number of goals.

Step by step:

  1. Multiply each value by its probability.

    E(X)=0(0.2)+1(0.5)+2(0.2)+3(0.1)E(X) = 0(0.2) + 1(0.5) + 2(0.2) + 3(0.1)E(X)=0(0.2)+1(0.5)+2(0.2)+3(0.1)
  2. Add the terms.

    =0+0.5+0.4+0.3=1.2= 0 + 0.5 + 0.4 + 0.3 = 1.2=0+0.5+0.4+0.3=1.2
Final answer:

E(X) = 1.2 goals (a mean can be a value X never actually takes).

IB-style question — is the game fair?

At a stall you pay $3 to spin a wheel. You win $10 with probability 0.2, otherwise you win nothing. Find the expected net gain per play and state whether the game is fair.

Step by step:

  1. Use the NET gain: +$7 if you win ($10 − $3 stake), −$3 if you lose.

    E(X)=7(0.2)+(−3)(0.8)E(X) = 7(0.2) + (-3)(0.8)E(X)=7(0.2)+(−3)(0.8)
  2. Work it out.

    =1.4−2.4=−1.0= 1.4 - 2.4 = -1.0=1.4−2.4=−1.0
  3. Compare with 0. A fair game needs E(X) = 0.

    E(X)=−1.0≠0E(X) = -1.0 \ne 0E(X)=−1.0=0
Final answer:

Expected net gain = −$1.00 per play, so the game is not fair (it favours the stall).

AA exam practice: key methods

Question typeRemember
two unknown probabilitiesThe probabilities sum to 1; the products xP(X = x) sum to E(X). These are different equations.
ranges of probabilities and E(X)Check every probability. Do not assume the expected value increases with the parameter; inspect its coefficient.

What you'll learn in Topic 4.7

  • 4.7.1 Discrete random variables & probability distributions
  • 4.7.2 Building probability distributions
  • 4.7.3 Expected value
  • 4.7.4 Fair games & expected money
  • 4.7.5 Expected value in decisions
  • 4.7.6 Repeated trials & expected outcomes
Suggested study order: Read the notes for each sub-topic below → test yourself with flashcards → attempt practice questions → review exam technique.

Study resources — 4.7 Discrete random variables

4.7.1

Discrete random variables & probability distributions

Notes
4.7.2

Building probability distributions

Notes
4.7.3

Expected value

Notes
4.7.4

Fair games & expected money

Notes
4.7.5

Expected value in decisions

Notes
4.7.6

Repeated trials & expected outcomes

Notes

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Topic 4.7 Discrete random variables forms a core part of Unit 4: Statistics & Probability in IB Math AA HL. Mastering these concepts will strengthen your understanding of connected topics across the syllabus and prepare you for exam questions that require analysis, evaluation, and real-world application.

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