Repeated Chance Experiments
One spin tells little
A single trial of a chance experiment — one spin, one flip, one roll — gives a single outcome that cannot be predicted for certain, and on its own it tells you very little. You cannot judge whether a spinner is fair from one spin. The interesting patterns of chance only appear when an experiment is repeated many times. That is why this unit is about repeated experiments: a single result is just a starting point, and the real learning comes from doing it again and again and watching what builds up.
Repeating the experiment
Repeating a chance experiment means doing the same trial many times and tallying the outcomes. Spin a three-colour spinner ten, twenty, fifty times and the counts for each colour build up. As they grow, relationships between the outcomes begin to show — which are about equally likely, which are rarer. Conducting repeated experiments, named directly in the descriptor, is the heart of this unit, because only by repeating can a child observe how outcomes relate, rather than guessing from a single try.
More trials, steadier results
A striking pattern appears with many repeats: the more trials, the closer the results tend to come to the expected pattern. Flip a fair coin ten times and heads might be 60 percent; by a thousand flips it settles close to 50 percent. Each extra trial steadies the overall share. This does not mean a run cannot stray — it means that, in the long run, results tend toward what is expected. Seeing this relationship between number of trials and steadiness is a key observation from repeated experiments.
Results vary
At the same time, repeated experiments show variation: run the same ten-spin experiment several times and each run comes out differently — red 4 then 2 then 3, and so on. This difference from run to run is variation, and it is completely normal in chance. Identifying and describing variation is written into the descriptor. Variation is not a mistake or a broken spinner; it is the natural unpredictability of chance, and learning to expect and describe it is as important as seeing the long-run pattern.
Predict, then test
Repeated experiments become powerful when paired with a prediction. Before running, work out what to expect: a fair coin flipped 20 times should give about 10 heads; a die rolled 60 times, about 10 of each number. Then run the experiment and compare. The real results will vary around the prediction rather than match it exactly, and that gap is the variation. Predicting then testing turns repeated experiments into a way of checking ideas about chance, joining what is expected to what actually happens.
Variation and the long run
Pulling the unit together, repeated chance experiments reveal two things at once: results vary from run to run, yet combined results settle toward the expected pattern. A table of runs makes this clear — 6, 4 and 5 heads out of 10 vary widely, but all 30 flips together give 15 out of 30, right at half. Holding both ideas — run-to-run variation and long-run steadiness — is the key understanding. With experiments repeated, the trials-and-steadiness pattern seen, variation described, and predictions tested, a child grasps how chance behaves over many trials, the goal of Year 4 probability.