A spinner is used times. It lands on red times and on blue times. Complete a frequency table for the two outcomes and work out the relative frequency of red.
Probability
Notes and three levels of exam-style practice for each registered specification leaf in this section.
Open the printable packRecord, describe and analyse the frequency of outcomes of probability experiments using tables and frequency trees
- A frequency table records how often each outcome occurs; the frequencies should add to the total number of trials.
- On a frequency tree, subtract from the parent frequency to complete a missing branch, then check that the two child branches add back to their parent.
- For example, if trials split into frequencies and , and of the first group succeed, the other frequency in that group is .
- Do not put probabilities on a frequency tree when frequencies are requested, and do not compare raw frequencies when the group totals are different.
Tier 1 · Easy
Tier 2 · Standard
A frequency tree describes visits to a kiosk. On visits a hot drink is chosen and on the remaining visits a cold drink is chosen. A snack is also bought on hot-drink visits and on cold-drink visits. Complete all terminal frequencies and work out the percentage of visits on which a snack is bought.
Tier 3 · Hard
Two weeks of trials are combined. In week 1, of trials succeed; successful trials and unsuccessful trials are fast. In week 2, of trials succeed; successful trials and unsuccessful trials are fast. Construct a combined frequency table for success or failure against fast or not fast. Compare the proportions that are fast in the two outcome groups.
Apply ideas of randomness, fairness and equally likely events to calculate expected outcomes of multiple future experiments
- Randomness means that an individual result is uncertain even when the long-run pattern can be predicted.
- For equally likely outcomes, calculate an event probability by dividing favourable outcomes by total outcomes, then use expected frequency for future trials.
- A fair game gives participants equal chances or has zero expected gain after any cost; fairness must be justified from the probabilities and rewards.
- An expected frequency is a long-run prediction, not a guarantee that exactly that many outcomes will occur.
Tier 1 · Easy
A fair six-sided die is rolled times. Work out the expected number of rolls on which the score is greater than .
Tier 2 · Standard
A fair spinner has four equal sectors labelled , , and . It is spun times. Work out the expected total of all the scores.
Tier 3 · Hard
A box contains green, yellow and red token. A token is chosen at random and replaced. A player receives for green, for yellow and nothing for red. The entry fee is . Work out the organiser's expected profit from plays and decide whether the game is fair to the player.
Relate relative expected frequencies to theoretical probability, using appropriate language and the 0-1 probability scale
- Probability lies from to : means impossible, means certain, and values nearer describe more likely events.
- Relative frequency is observed frequency divided by number of trials; theoretical probability comes from a mathematical model of the outcomes.
- If a theoretical probability is , the relative frequency from many unbiased trials is expected to be close to , although it will usually not equal it exactly.
- Do not describe an event with probability as certain, and do not treat a small experimental difference as proof that a theoretical model is wrong.
Tier 1 · Easy
Place these events in order from least likely to most likely: event A has probability , event B has probability , and event C has probability .
Tier 2 · Standard
An outcome occurs times in trials. Its theoretical probability is . Work out the relative frequency and the expected frequency in further trials. Comment on the experimental result.
Tier 3 · Hard
A model says that a device flashes with probability on each trial. In a short run it flashes times in trials. After trials in total it has flashed times. Calculate both relative frequencies and decide which result gives stronger evidence about the model.
Apply the property that the probabilities of an exhaustive set of outcomes sum to one; apply the property that the probabilities of an exhaustive set of mutually exclusive events sum to one
- An exhaustive set covers every possible outcome, so its probabilities have total .
- Mutually exclusive events cannot occur together; for such events, add their probabilities to find the probability that any one occurs.
- The complement rule is , which treats and not as an exhaustive, mutually exclusive pair.
- Do not add probabilities directly when events can overlap; first separate the overlap or subtract it once using .
Tier 1 · Easy
The probability that a parcel arrives early is . Work out the probability that it does not arrive early.
Tier 2 · Standard
A trial has four mutually exclusive outcomes A, B, C and D. Their probabilities are , , and respectively. Work out .
Tier 3 · Hard
For two events A and B, , and . Work out the probability that neither A nor B occurs.
Understand that empirical unbiased samples tend towards theoretical probability distributions, with increasing sample size
- An empirical distribution is built from observed relative frequencies, whereas a theoretical distribution is predicted from a probability model.
- With unbiased, independent trials, increasing the sample size usually makes empirical proportions settle nearer their theoretical probabilities.
- For a fair die, a large sample should give each score a relative frequency near , but exact equality is not required.
- A larger sample reduces random variation but does not repair a biased sampling method or guarantee a closer result on every single run.
Tier 1 · Easy
A fair coin gives a relative frequency of heads of after tosses. Explain what is likely to happen to the relative frequency as many more unbiased tosses are made.
Tier 2 · Standard
A spinner is designed to land on green with probability . It lands on green times in spins and times in spins. Compare the two empirical probabilities with the theoretical probability.
Tier 3 · Hard
A fair die is tested. In the first rolls, a six appears times. After rolls in total, a six has appeared times. A student says the die must be biased because neither relative frequency equals . Evaluate the student's claim.
Enumerate sets and combinations of sets systematically, using tables, grids, Venn diagrams and tree diagrams
- Systematic enumeration lists every permitted outcome once, using a consistent order so omissions and duplicates are visible.
- Use a table or grid for two varying quantities, a tree for successive choices, and a Venn diagram for membership of overlapping sets.
- For two sets, place the intersection first, then the parts belonging only to each set, and finally the values outside both sets.
- Do not assume all listed outcomes are equally likely; enumeration identifies possibilities, while probability also depends on the model.
Tier 1 · Easy
A uniform is made from one of two shirts, blue or white, and one of three ties, red, silver or green. List all possible shirt-and-tie combinations.
Tier 2 · Standard
The universal set is the integers from to . Set A contains the multiples of and set B contains the factors of . Enumerate the four regions of a Venn diagram for A and B.
Tier 3 · Hard
A three-digit number is formed from three different digits chosen from , , and . Enumerate all the numbers that are greater than and even. How many of these numbers do not contain the digit ?
Construct theoretical possibility spaces for single and combined experiments with equally likely outcomes and use these to calculate theoretical probabilities
- A possibility space displays every combined outcome, often as ordered pairs in a grid.
- When all elementary outcomes are equally likely, probability is favourable outcomes divided by the total number of outcomes in the space.
- For two fair choices with and outcomes, a complete rectangular space has ordered pairs before restrictions are applied.
- Do not count unordered pairs when the experiment records a first and second result; and are different ordered outcomes unless the context says otherwise.
Tier 1 · Easy
A fair coin is tossed and a fair spinner labelled , , is spun. Write the six outcomes as ordered pairs and find the probability of getting a head and an even number.
Tier 2 · Standard
Spinner A has equal sectors labelled , , . Spinner B has equal sectors labelled , , , . Construct a possibility space and find the probability that the two scores have a sum greater than .
Tier 3 · Hard
Two different cards are chosen in order from cards labelled , , , and . The first card is the tens digit and the second is the units digit. Construct the theoretical possibility space and find the probability that the two-digit number is divisible by .
Calculate the probability of independent and dependent combined events, including using tree diagrams and other representations, and know the underlying assumptions
- For events along one route through a tree, multiply branch probabilities; for alternative mutually exclusive routes, add their products.
- Independent events leave later probabilities unchanged, while dependent events change later probabilities because earlier outcomes affect the situation.
- Without replacement, update both numerator and denominator after each draw; with replacement, the original probabilities repeat.
- Do not multiply probabilities without checking the assumptions: identical branch probabilities require independence or a replacement mechanism.
Tier 1 · Easy
A fair coin is tossed and an independent spinner lands on red with probability . Work out the probability of a head and red.
Tier 2 · Standard
A bag contains blue counters and amber counters. Two counters are chosen at random without replacement. Work out the probability that both counters are blue.
Tier 3 · Hard
A bag contains black and white counters. Three counters are chosen at random without replacement. Work out the probability that exactly two are black. State why the branch probabilities change after each choice.
Calculate and interpret conditional probabilities through representation using expected frequencies with two-way tables, tree diagrams and Venn diagrams [Higher only]
- A conditional probability restricts the sample space to outcomes satisfying the stated condition.
- In a two-way table or Venn diagram, calculate by dividing the frequency in both and by the total frequency in .
- Expected frequencies can replace probabilities on a tree; after multiplying each branch by a common starting total, condition using the relevant terminal frequencies.
- Do not divide by the overall total when a condition is given: the denominator must be the frequency of the conditioning event.
Tier 1 · Easy
A two-way table records students. Of the who travel by bus, arrive late. Find the probability that a randomly chosen bus traveller arrives late.
Tier 2 · Standard
Of expected customers, are members. Of the members, order online. Of the non-members, order online. Use expected frequencies to find the probability that an online customer is a member.
Tier 3 · Hard
In an expected-frequency Venn diagram for people, are in set A, are in set B and are in both sets. A person is chosen from those who are in exactly one of the sets. Find the conditional probability that the person is in A.