How do we describe and measure the chance of an event in words and as a number between 0 and 1?
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.
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What this dot point is asking
NESA wants you to talk about chance in two matching languages and to move smoothly between them. The first is the everyday language of likelihood: words such as impossible, unlikely, even chance, likely and certain. The second is the number language: every chance is a number between and , where means it never happens and means it always happens. You need to place an event on this likelihood scale, describe it with the right word, and connect that word to the right number. You also need to know what makes a situation fair (all outcomes equally likely) or biased (they are not), because almost every probability you calculate later in the course relies on the outcomes being equally likely. This is the vocabulary the whole module is built on, so getting the words and the scale exactly right here pays off everywhere.
The answer
Chance is measured on a single scale that runs from to . An event that can never happen has a probability of ; an event that is sure to happen has a probability of ; and everything else sits somewhere in between. The closer the number is to , the more likely the event. The words you use in conversation map onto fixed points on this scale, and the number line below shows where each one sits.
The likelihood scale in words
Long before you put a number on a chance, you can describe it in plain English. The five words below are the ones NESA expects, listed from least to most likely:
- impossible - the event can never happen (probability ),
- unlikely - the event happens on less than half of occasions (probability between and , around for "about one chance in four"),
- even chance - the event is just as likely to happen as not, a fifty-fifty (probability ),
- likely - the event happens on more than half of occasions (probability between and , around ),
- certain - the event is sure to happen (probability ).
You will also meet softer phrases such as "very unlikely" (close to ) and "almost certain" (close to ). They simply slide further toward the ends of the scale.
Describing chance as a number between 0 and 1
Every chance can also be written as a number, and that number is always between and :
A probability can be written as a fraction, a decimal or a percentage, and these are three ways of saying the same thing. An even chance is . A "likely" event around three quarters of the way up is . The advantage of the number is precision: "likely" covers everything from to , but pins down exactly how likely. A number outside the range to , such as or , is not a probability at all and signals a mistake.
Equally likely outcomes
An outcome is a single possible result, such as one particular face of a die or one colour on a spinner. Outcomes are equally likely when each has the same chance of occurring. The faces of a balanced die are equally likely; so are the two sides of a fair coin and the equal sectors of a spinner. Equally likely outcomes are the foundation of theoretical probability, because only then can you find a probability simply by counting: the chance of an event is the number of favourable outcomes out of the total number of equally likely outcomes. If the outcomes are not equally likely (a spinner with one huge sector, say), counting alone will not give the right answer.
Fair versus biased
A device is fair when all of its outcomes are equally likely, and biased when they are not. A standard six-sided die is fair because the cube is symmetric, so no face is favoured. A coin that has been bent, a die that has been weighted on one side, or a spinner with unequal sectors is biased, because some outcomes now come up more often than others. The word "fair" is a promise that you may treat the outcomes as equally likely; "biased" is a warning that you may not. When a real experiment gives results that are wildly different from what a fair device would predict (for example heads in tosses), that is evidence the device is biased.
How exam questions ask about the language of probability
The wording is varied but each version is one of a few standard tasks:
- "Describe the likelihood / chance of ... in words." Choose the right word from impossible, unlikely, even chance, likely or certain. Decide by where the chance sits relative to a half.
- "Match the description to a probability" or "place the event on the scale." Connect the word to its number (, around , , around , ) and mark its position on the to line.
- "Is the ... fair or biased? Justify your answer." State fair or biased, then justify it by saying whether the outcomes are equally likely and why (symmetry for fair; weighting, shape or unequal sectors for biased).
- "Are the outcomes equally likely?" Yes only if each has the same chance (equal sectors, a symmetric die); otherwise no, and say which outcome is favoured.
- "Give a reason" is the command that earns the second mark: never just write "likely", always add the brief why ("because it happens on more than half of occasions").
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-style3 marksA spinner is divided into coloured sectors: red fills one half of the spinner, while blue and green each fill one quarter. The spinner is spun once. (a) Are the three colours equally likely? Justify your answer. (b) Describe in words the chance of the spinner landing on blue, supporting your answer with a probability. (c) Describe in words the chance of landing on either red or blue.Show worked answer →
Part (a): not equally likely, because the sectors are different sizes - red covers half while blue and green each cover only a quarter - so red is more likely than blue or green. The justification (unequal sector sizes) is required for the mark, not just "no".
Part (b): blue fills one quarter, so , which is below a half, so landing on blue is unlikely. Markers want both the value and the word "unlikely".
Part (c): red plus blue covers one half plus one quarter , so red-or-blue is likely. Award the final mark for with the word "likely". A common loss is calling blue "even chance" by confusing it with the fifty-fifty red sector.
2022 HSC-style4 marksAn ordinary fair six-sided die is rolled once. (a) Explain what it means for the die to be fair. (b) Describe in words, with a reason, the chance of rolling a number greater than . (c) Describe in words, with a reason, the chance of rolling a . (d) A second die always lands on no matter how it is rolled. Is this die fair or biased? Justify your answer.Show worked answer →
Part (a): fair means all six faces are equally likely, because the cube is symmetric so no face is favoured. The phrase "equally likely" is the key idea markers look for.
Part (b): the faces greater than are , which is of the faces, so . As this is well above a half, the event is likely (almost certain). The reason - five of the six faces succeed - earns the second mark.
Part (c): only one face shows a , so , which is below a half, so it is unlikely. Again the count "one face out of six" is the required reason.
Part (d): biased, because the outcomes are not equally likely - one face (the ) always comes up while the others never do. Markers reward the verdict "biased" plus the equally-likely justification; "biased" alone is not enough for full marks.
Practice questions
Original practice questions graded from foundation to exam level, each with a full worked solution. Try them before revealing the solution.
foundation2 marksDescribe the likelihood of each event in words, choosing from impossible, unlikely, even chance, likely or certain. (a) Rolling a number less than on an ordinary six-sided die. (b) Tossing a fair coin and getting a head.Show worked solution →
Part (a) - check every outcome. An ordinary die shows or , and every one of these is less than . The event always happens, so it is certain (a probability of ).
Part (b) - count the equally likely outcomes. A fair coin has two equally likely outcomes, a head or a tail, and exactly one of them is a head. A head happens on half of all tosses, so a head is an even chance (a probability of ). (Sanity check: "certain" sits at the right-hand end of the likelihood scale and "even chance" sits in the middle, which matches a guaranteed event and a fifty-fifty event.)
foundation2 marksMatch each worded description to the probability that fits it best from the list , , , , . (a) An impossible event. (b) An event with an even chance. (c) A certain event.Show worked solution →
- Use the likelihood scale
- Probabilities run from (impossible) to (certain), with the words spread evenly across the scale.
- Part (a) impossible
- An impossible event never happens, so its probability is .
- Part (b) even chance
- An even chance is fifty-fifty, halfway along the scale, so its probability is .
- Part (c) certain
- A certain event always happens, so its probability is . (The two left-over values, and , are "unlikely" and "likely" respectively, which is worth remembering for the next question.)
foundation2 marksA spinner is divided into four equal coloured sectors: red, blue, green and yellow. (a) Are the four outcomes equally likely? Give a reason. (b) Describe in words the chance of the spinner landing on red.Show worked solution →
Part (a) equal sectors mean equal chance. The four sectors are the same size, so the pointer has the same chance of stopping on each one. The outcomes are therefore equally likely.
Part (b) one favourable outcome out of four. Red is one of four equally likely results, so it happens on one quarter of the spins. A probability of sits a quarter of the way along the scale, which is described as unlikely. (Check: four equally likely colours must share the whole certainty of between them, and , so each colour having a probability of is consistent.)
core3 marksDecide whether each situation is fair or biased, and justify each answer. (a) A standard six-sided die used in a board game. (b) A drawing pin tossed to see if it lands point-up or point-down. (c) A raffle in which one person has bought of the tickets sold.Show worked solution →
- Fair means every outcome is equally likely; biased means it is not
- Part (a) the die
- A standard die is a symmetric cube, so each face has the same chance of landing up. The outcomes are equally likely, so the die is fair.
- Part (b) the drawing pin
- A drawing pin is not symmetric: its heavy flat head and light point make point-up and point-down land at different rates. The two outcomes are not equally likely, so this is biased.
- Part (c) the raffle
- Each ticket is equally likely to be drawn, so at the level of single tickets the draw is fair. But the people are not equally likely to win: the person holding of the tickets has a chance, far more than someone with one ticket. So while the draw itself is fair, the chances between people are biased toward the big buyer. (The key test in every part is the same: ask whether the outcomes you are comparing are equally likely.)
core3 marksAn ordinary fair six-sided die is rolled once. For each event, give the probability as a fraction in simplest form and then describe it in words (impossible, unlikely, even chance, likely or certain). (a) Rolling an even number. (b) Rolling a number greater than . (c) Rolling a .Show worked solution →
There are six equally likely outcomes. The faces are , so each probability is the count of favourable faces divided by .
Part (a) an even number. The even faces are , which is faces:
A probability of is an even chance.
Part (b) greater than . The faces greater than are and , which is faces:
A probability of about is below a half, so this event is unlikely.
Part (c) a . No face shows a , so it cannot happen:
which is impossible. (Check: lies between and , so "unlikely" is the right word, sitting left of the midpoint of the scale.)
exam5 marksA bag holds marbles: red, blue and green. One marble is drawn at random. (a) Explain what "drawn at random" tells you about the outcomes. (b) Find the probability of drawing a green marble, as a decimal. (c) Describe the chance of drawing a green marble in words. (d) Describe the chance of drawing a blue marble in words, supporting your answer with its probability. (e) Is drawing a red marble more or less likely than an even chance? Justify your answer.Show worked solution →
Part (a) what "at random" means. Drawing at random means every marble has the same chance of being selected, so the outcomes are equally likely at the level of individual marbles. The colours are not equally likely, because there are different numbers of each.
Part (b) probability of green. There are green marbles out of :
Part (c) green in words. A probability of is more than a half but not certain, so drawing a green marble is likely.
Part (d) blue in words. There are blue marbles out of :
which is well below a half, so drawing a blue marble is unlikely.
Part (e) red compared with an even chance. There are red marbles out of :
Since , drawing a red marble is less likely than an even chance. (Check: the three probabilities are , as they must be, because every draw lands on red, blue or green.)
exam5 marksA teacher claims a coin is fair. The class tosses it times and records heads and tails. (a) For a genuinely fair coin, describe in words the chance of a head and state its probability. (b) Compare the recorded results with what a fair coin would predict. (c) Does the evidence suggest the coin is fair or biased? Justify your answer. (d) Place both the claimed probability of a head and the result actually observed for a head on the to scale, and describe each in words.Show worked solution →
Part (a) a fair coin. A fair coin has two equally likely outcomes, so a head has an even chance, a probability of
- Part (b) compare with the prediction
- For a fair coin, tosses would give roughly heads. The class recorded heads, which is far more than , and only tails instead of about .
- Part (c) fair or biased
- The results are nowhere near the fifty-fifty split a fair coin produces over many tosses, so the evidence suggests the coin is biased toward heads. (One run can wander a little from the prediction, but out of is far too lopsided to be ordinary variation.)
- Part (d) on the scale
- The claimed probability of a head is , an even chance, sitting at the midpoint of the scale. The observed proportion of heads is
which sits near the right-hand end, well past "likely" and close to "certain". The gap between and on the scale is the picture of the bias. (Check: , the head and tail proportions adding to as they must.)
Related dot points
- 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.
- 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.
- 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.