Math // Probability
Probabilities Sum to One
Understand that when all possible outcomes of a trial are listed, their probabilities must add up to 1; use this to find the probability of an event NOT happening: P(not A) = 1 − P(A); apply this shortcut to avoid counting all unfavourable outcomes directly
Quick check
If the probability of it raining tomorrow is 0.3, can the learner work out the probability of it NOT raining — and explain why all probabilities in a situation must add up to 1?
Ask this to see whether the topic is secure.
Topic // Mastery
What mastery looks like
- List all outcomes of spinning a 4-colour spinner and verify their probabilities add up to 1
- Calculate P(not rolling a 3) as 1 − 1/6 = 5/6 using the complement rule
- Spot an error in a probability table where the values don't sum to 1 and explain what's wrong
Topic // Map
Where this fits
- RequiredMust come first
- HelpfulHelps, but not essential
Before this
2 topics- The 0-to-1 Probability ScaleRequired
Probability // Ages 10 to 11
The complement rule P(not A) = 1 − P(A) requires understanding probability as a number that lies between 0 and 1
Probability // Ages 10 to 11
Using the complement rule is easier once students can calculate basic probabilities and see that favourable + unfavourable outcomes cover all possibilities
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Probabilities Sum to One
Ages 10 to 11 // Concept
Leads to
1 topic- Complementary eventsRequired
Probability // Ages 11 to 13
The formal mutually-exclusive outcomes rule extends the simpler complement rule introduced at age 10-11
Topic // Research-informed
Teaching notes
From the Marble Skill Taxonomy. These notes have not been validated in classrooms, so treat them as a starting point for your own judgement.
The approach
Teach that when you list ALL the possible outcomes of a trial — with no overlaps and nothing left out — their probabilities must total exactly 1. This lets a learner find a missing probability, or the probability of an event NOT happening, by subtracting from 1 (P(not A) = 1 − P(A)) instead of counting every unfavourable outcome. The reasoning only holds when the outcomes are mutually exclusive (no overlap) and exhaustive (cover everything).
Common misconceptions
- Ignoring the sum-to-1 constraint and assigning a missing outcome an arbitrary or 'equal' value by analogy to another
- Treating 'not A' as a single other outcome rather than everything except A, or thinking P(not A) equals P(A)
- Adding probabilities of overlapping or non-exhaustive events and still expecting them to total 1
- Adding fractions without a common denominator when totalling probabilities
Useful representations
- Unit bar (length 1) partitioned into outcome segments
- Complete outcome table with probabilities totalling 1
- P(not A) shown as the remaining part of the whole
- Spinner whose sectors fill the entire disc
Teaching practices
- Model the whole of possibility as a bar of length 1 partitioned among the outcomes, so 'the rest of the bar' IS the complement
- Establish that the list must be exhaustive (covers everything) and mutually exclusive (no overlaps) before the sum-to-1 argument applies
- Teach P(not A) = 1 − P(A) as a shortcut, contrasting it with the slower count-all-the-others method on the same problem
- Use spot-the-error tables whose probabilities don't total 1, and ask what must be wrong
- Link back to calculating simple probabilities so children see favourable + unfavourable together exhaust the outcomes
Activities to try
- 1
Fill the unit bar: the leftover IS the missing probability
Why it works: The whole of possibility has length 1; once some outcomes are placed, the leftover segment IS the missing probability, and 'not red' is the whole rest of the bar — everything except red — not a single other colour.
- Take a bar exactly one unit long that stands for everything that can happen when you draw a counter from a bag of red, blue and green counters.
- Set red to one-half of the bar and blue to one-sixth, marking those segments.
- Before being told, work out what must fill the remaining strip and state it: green = 1 − (1/2 + 1/6) = 1 − 2/3 = 1/3.
- Mark 'P(not red)' by highlighting the entire rest of the bar (blue and green together) and give its value as 1 − P(red) = 1/2.
- State in words why green could NOT be a free choice and why 'green must be 1/6 like blue' is wrong.
- 2
Spinner that fills the whole disc
Why it works: A spinner's sectors are another model of the whole-equals-1 idea: because the sectors must fill the disc, the last sector's size (and probability) is forced by the others.
- Look at (or draw) a spinner whose coloured sectors must fill the entire disc with no gap and no overlap.
- Given red = one-half and blue = one-third, predict the remaining sector's probability (yellow) before it is revealed: 1 − (1/2 + 1/3) = 1/6.
- Check the revealed sector really is a sixth of the disc.
- Tap or mark each sector in turn and track the running total as it reaches exactly 1.
- 3
Complement shortcut versus counting the others
Why it works: P(not A) = 1 − P(A) is a shortcut for 'everything except A', and it equals the sum of all the other outcomes because together they fill the whole; the same subtraction works when the known part is a compound event like 'red or blue'.
- Calculate P(not rolling a 3) on a fair six-sided die two ways: first by subtracting, 1 − 1/6 = 5/6; then by counting all the other outcomes (1,2,4,5,6) and adding their probabilities (five sixths).
- Compare the two methods, note they give the same answer, and that subtracting from 1 is faster when there are many unfavourable outcomes.
- For the counter bag, find P(not red) as 1 − P(red) = 1/2 and confirm it matches blue + green (1/6 + 1/3 = 1/2).
- Extend to a compound complement: a different bag of red, blue and green counters has P(red or blue) = 3/4; find P(green) = 1 − 3/4 = 1/4, since each counter is exactly one of the three colours and the three colours exhaust the bag.
Math // Probability
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