Why does every probability lie between 0 and 1, and how do complementary events help you find a chance the short way?
Recognise that probabilities of events range from 0 to 1, identify the complement of an event and use the relationship that the probability of an event and its complement sum to 1, so the probability of 'not E' equals 1 minus the probability of E
A focused answer to the HSC Maths Standard 2 dot point on the range of probabilities and complementary events. Why every probability sits between 0 and 1, what the complement of an event is, the rule that an event and its complement add to 1 so the probability of not E is 1 minus the probability of E, and the at-least-one short cut, with worked Australian examples.
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What this dot point is asking
NESA wants you to know two firmly linked facts about every probability. First, a probability is always a number from to inclusive: nothing can be less likely than impossible () or more likely than certain (). Second, every event has a complement, written (sometimes or ), meaning " does not happen", and the two chances always add to . That single relationship, , is one of the most useful tools in the whole probability module. It turns a hard "find the chance that something happens" into an easy "find the chance it does not, then subtract from ", which is exactly how the dreaded "at least one" questions are meant to be done.
The answer
Probability measures how likely an event is on a fixed scale from to . An impossible event scores , a certain event scores , and an even chance scores . Because the favourable outcomes can never be fewer than none nor more than all of the sample space, the count fraction is always between and :
Every event also has a complement , the event that does not occur. Between them, and cover every possible outcome exactly once - one of them must happen, and they cannot both happen - so their probabilities fill the whole scale and add to . Rearranging gives the rule you will use constantly.
Why every probability lies between 0 and 1
A probability is the fraction of outcomes that count as favourable: . The number of favourable outcomes can be as small as (none of them happen, an impossible event) or as large as (all of them happen, a certain event), but never outside that range. Dividing through:
- if then , the event is impossible,
- if then , the event is certain,
- otherwise is a fraction strictly between and .
So a probability is never negative and never more than . If a calculation ever gives you or , you have made an error somewhere, because no real event can be more certain than certain. This bound is also a quick self-check on any answer.
The complement of an event
The complement of an event is the event " does not happen", written (you may also see or ). If is "roll a " then is "roll a or ". Two facts make the complement so useful:
- and together include every outcome in the sample space, and
- they share no outcome (an outcome cannot both be and not be in ).
So between them they account for the whole sample space exactly once. That is why their probabilities add to :
Rearranging gives the working form of the rule, and the reverse:
For the die, , so . The complement bar above is just this rule drawn to scale: the whole bar is , and the two coloured parts are and .
When the complement is the easy road: "at least one"
The complement earns its keep on questions that ask for the probability of "at least one" of something. Listing every way to get one, two, three or more successes is slow and error-prone. But the opposite of "at least one" is simply "none", a single case. So
For example, toss a fair coin twice. "At least one head" is the complement of "no heads". The only no-head outcome is , with probability , so
Whenever you see "at least one", reach for the complement first. The harder the count of the "at least one" cases, the bigger the saving.
How exam questions ask about the range and complement
The wording is varied, but each phrasing points to the same small set of moves:
- "Find the probability that ... does not / is not ..." is a straight complement: compute , then .
- "... none / neither ..." is also a complement of an "at least one" event, or a single multiply-the-misses case.
- "... at least one ..." is the signal to use rather than adding cases.
- "Explain why (or ) is impossible" wants the bound quoted, with "no event is more likely than certain or less likely than impossible".
- "Find the remaining probability / the missing value" uses that all the outcomes' probabilities add to , so the missing one is minus the rest.
- "Show that the values are (not) valid probabilities" wants you to check each is between and and, for a complete set, that they sum to .
Exam-style practice questions
Practice questions written in the style of NESA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
2021 HSC-style2 marksThe probability that a bus is late on any given morning is . (a) Find the probability that the bus is not late on a given morning. (b) State the largest value a probability can take and the smallest.Show worked answer →
Part (a): the bus being not late is the complement of being late, so . One mark for the correct complement.
Part (b): the largest value is (a certain event) and the smallest is (an impossible event), so every probability satisfies . One mark for both bounds.
Markers reward the explicit subtraction from for the complement and both correct bounds. A common loss is writing without showing , or giving only one of the two bounds.
2022 HSC-style3 marksA fair coin is tossed times. (a) Find the probability of obtaining no heads. (b) Hence find the probability of obtaining at least one head. (c) Briefly explain why the complement is the efficient method here.Show worked answer →
Part (a): the eight equally likely outcomes range from to ; only has no heads, so . Equivalently . One mark.
Part (b): "at least one head" is the complement of "no heads", so . One mark.
Part (c): "at least one head" covers exactly one, two or three heads (seven of the eight outcomes), so the complement replaces three separate counts with the single case . One mark for a clear reason.
Markers reward the word "complement" and the subtraction . The standard error is trying to add the cases directly and miscounting, or forgetting that "at least one" includes the all-heads case.
2023 HSC-style3 marksA box contains light globes, of which are faulty. One globe is selected at random. (a) Find the probability that the selected globe is faulty. (b) Find the probability that it is not faulty. (c) A student writes and . Identify and correct the error.Show worked answer →
Part (a): of the globes are faulty, so . One mark.
Part (b): "not faulty" is the complement, so (equivalently ). One mark.
Part (c): a probability and its complement must add to , but . The error is the complement: it should be , not . One mark for identifying that the pair fails to sum to and giving the correct .
Markers reward checking that the two probabilities sum to as the test for the error, and the corrected value .
Practice questions
Original practice questions graded from foundation to exam level, each with a full worked solution. Try them before revealing the solution.
foundation2 marksA bag holds red, blue and green marbles. One marble is drawn at random. (a) Find the probability that it is blue. (b) Find the probability that it is not blue.Show worked solution →
Count the sample space. There are marbles in all.
Part (a) - probability of blue. Five of the marbles are blue, so
Part (b) - probability of not blue, by the complement. "Not blue" is the complement of "blue", so subtract from :
(Check by counting directly: marbles are not blue, and , which agrees.)
foundation2 marksThe probability that it rains in a town on a given June day is . Find the probability that it does not rain that day.Show worked solution →
Recognise the complement. "It does not rain" is the complement of "it rains", and the two probabilities must add to .
Subtract from .
so the probability of no rain is . (Sanity check: , as a probability and its complement must.)
foundation2 marksA standard six-sided die is rolled once. (a) Find the probability of rolling a number greater than . (b) Hence find the probability of rolling a number that is not greater than .Show worked solution →
List the sample space. The faces are , so equally likely outcomes.
Part (a) - greater than . The favourable faces are and , so
Part (b) - not greater than , by the complement. Subtract from :
(Check directly: the faces are not greater than , giving , which matches.)
core3 marksA spinner is divided into sectors coloured red, blue, yellow and green. The probabilities are , and . (a) Explain why these three values alone cannot describe a fair four-colour spinner unless green is also possible. (b) Find .Show worked solution →
Part (a) - the total must be . For one spin exactly one colour occurs, so the probabilities of all the outcomes must add to . The three given values total
which is less than , so the remaining probability of must belong to green; the spinner cannot be described by the first three alone.
Part (b) - find as the complement of the other three. Green is "none of red, blue or yellow", so
(Check: , so the four probabilities form a complete set.)
core3 marksA fair coin is tossed twice. (a) List the sample space. (b) Find the probability of getting no heads. (c) Hence find the probability of getting at least one head.Show worked solution →
Part (a) - the sample space. Writing for heads and for tails, the four equally likely outcomes are
so .
Part (b) - no heads. The only outcome with no heads is , so
Part (c) - at least one head, by the complement. "At least one head" is the complement of "no heads", so
(Check by listing: each contain a head, so agrees - and the complement saved counting all of them.)
exam5 marksOn a production line each item is faulty independently with probability . A quality inspector takes a sample of items. (a) Find the probability that none of the items is faulty. (b) Find the probability that at least one of the items is faulty, correct to four decimal places. (c) Explain why using the complement is far easier here than adding the chances of exactly one, exactly two and exactly three faulty items.Show worked solution →
Part (a) - none faulty. Each item is not faulty with probability , and the three items are independent, so multiply:
Part (b) - at least one faulty, by the complement. "At least one faulty" is the complement of "none faulty", so
Correct to four decimal places, .
Part (c) - why the complement wins. "At least one" covers three separate cases (exactly one, exactly two, or exactly three faulty), each needing its own calculation, then a sum. The complement "none faulty" is a single case, so replaces three calculations with one. (Check: the direct cases would still total , but the complement reaches it in one line.)
exam5 marksA raffle sells tickets. Mia buys tickets and Sam buys tickets; one winning ticket is drawn at random. (a) Find the probability that Mia wins. (b) Find the probability that neither Mia nor Sam wins. (c) Find the probability that the winner is someone other than Mia, as a decimal. (d) A friend claims the probability that Mia wins is and the probability she does not win is . Explain the error.Show worked solution →
Part (a) - Mia wins. Mia holds of the equally likely tickets, so
Part (b) - neither Mia nor Sam wins. Together they hold tickets, so a win for one of them has probability . "Neither wins" is the complement of "Mia or Sam wins":
Part (c) - someone other than Mia wins. This is the complement of "Mia wins":
Part (d) - the error. A probability and its complement must add to exactly . The friend's pair gives , not , so it is impossible. The correct complement of is , matching part (c).
Related dot points
- Describe the likelihood of an event using the language of chance and the probability scale from 0 to 1, distinguishing fair from biased and equally likely outcomes
A focused answer to the HSC Maths Standard 2 dot point on the language of probability. The likelihood scale from impossible to certain, describing chance in words and as a number between 0 and 1, even chance, likely and unlikely, the meaning of fair versus biased, and equally likely outcomes, with worked Australian examples.
- List the sample space of equally likely outcomes and calculate the theoretical probability of an event using , the number of favourable outcomes divided by the total number of outcomes
A focused answer to the HSC Maths Standard 2 dot point on theoretical probability. Listing a sample space systematically, equally likely outcomes, the formula P(E) = n(E)/n(S), and finding the probability of single and described compound events on dice and cards, with worked Australian examples.
- Use arrays and tree diagrams to determine the outcomes and probabilities for multi-stage experiments, including two-way tables, multiplying probabilities along the branches of a tree diagram and adding the probabilities of mutually exclusive outcomes, with and without replacement
A focused answer to the HSC Maths Standard 2 dot point on multi-stage events. Two-way tables, tree diagrams for two- and three-stage experiments, the difference between drawing with and without replacement, multiplying probabilities along the branches and adding across mutually exclusive paths, with worked coin, counter and survey examples.
- Calculate relative frequencies to estimate probabilities of events, where relative frequency = frequency of the event divided by the total number of trials, recognising that as the number of trials increases the relative frequency approaches the theoretical probability
A focused answer to the HSC Maths Standard 2 dot point on relative frequency. Relative frequency as frequency divided by total, using it as an experimental probability, estimating the chance of a real event from collected data, and the long-run convergence of relative frequency toward the theoretical probability, with worked Australian examples.
- Calculate the expected frequency of an event from the probability of the event and the number of trials, using expected frequency = P(E) x number of trials
A focused answer to the HSC Maths Standard 2 dot point on expected frequency. The rule expected frequency = P(E) times the number of trials, predicting how many times an event should happen over many trials, the expected-versus-observed difference, and working backwards to find the number of trials from an expected count, with worked Australian examples.