The expected number of times an outcome happens is its probability × the number of trials: 60 rolls should give about 10 sixes. Run the experiment and record the counts: the results come close, but rarely exactly.
Roll a dice 60 times. Exactly ten sixes? Probably not. But how far off is normal, and when should you suspect the dice?
A probability lets you predict what should happen over many trials:
expected count=probability×number of trials
So in 60 rolls of a fair dice you expect about 60×61=10 sixes. Then you test it: run the experiment, record the counts in a table, and compare. The relative frequency (count ÷ trials) is the experiment's estimate of the probability.
Predict: Read the problem and decide what you think before you try anything. A wrong guess is fine: it shows you what to look for.
Try: Try it on the board and compare the result with your prediction.
Investigate: Work out why it happens, one step at a time.
Modify: Change the problem on purpose and see what happens.
Practise: A few on your own, to check you have it.
Make: Make your own problem using what you have learned. Expect a few tries; that is normal.
Make your prediction first. Help opens once you've locked it in.
PredictRead the problem and decide what you think before you try anything. A wrong guess is fine: it shows you what to look for.
How many sixes?
What fraction of rolls should be a six?
TryTry it on the board and compare the result with your prediction.
Roll 60 times
Compare with others: did anyone get exactly 10? What was the furthest from 10?
Try it yourselfYour edits are saved in this browser.
Roll 60 times (press Run 10 six times). How many sixes did you get? Was your prediction right?
Use the board. This ticks when you get there.
InvestigateWork out why it happens, one step at a time.
Expected and observed
Here is how to predict and test.
Worked exampleBefore each step, say what you think comes next.
P(6)=61The probability from the sample space.
60×61=10Expected count: probability × trials.
observed: 7 sixesRun the experiment and record the count.
607≈0.12Relative frequency = count ÷ trials, the experiment's estimate.
0.12 against 0.17Close but not equal: a short experiment varies.
Now: how many heads in 50 flips?
Read Noah's reasoning. Is 7 instead of 10 surprising for a fair dice?
You flip a fair coin 50 times. How many heads do you expect?
Noah tests a dice. Click the line where his reasoning goes wrong.
In an experiment, a coin landed heads 13 times in 20 flips. What is the relative frequency of heads? (A decimal.)
ModifyChange the problem on purpose and see what happens.
One change at a time
Each task changes one thing.
Need a hint?
Expected: 100 × 1/2 = 50 heads.
Need a hint?
Red is 3 of 8 equal parts. Run 80 spins and look at the expected count column.
Try it yourselfYour edits are saved in this browser.
Flip the coin 100 times. Compare the number of heads with the expected 50.
Use the board. This ticks when you get there.
A spinner is 83 red. How many reds do you expect in 80 spins?
Spin this spinner (3 red, 5 blue sectors) at least 80 times. Compare the reds with the expected count.
Use the board. This ticks when you get there.
PractiseA few on your own, to check you have it.
Expected counts
A bag has 2 red and 8 blue counters. You take one and put it back, 40 times. How many reds do you expect?
A spinner landed on green 18 times in 60 spins. What is the relative frequency of green? (A decimal.)
Review: roll a fair dice. What is P(a number less than 3)? Simplest form.
MakeMake your own problem using what you have learned. Expect a few tries; that is normal.
Plan an experiment
Then: how many spins of the 3-red, 5-blue spinner to expect 30 reds?
You want to expect 25 sixes from a fair dice. How many times should you roll it?
For teachers
Students predict expected counts (probability × trials), run experiments on a chance board, record counts and relative frequencies, and see that observed results vary around the expected count (AC9M7P01 node 3, AC9M7P02 node 1). About 45 minutes.
I can predict how often an outcome should happen in a number of trials.
I can run an experiment, record counts and work out relative frequencies.
I can explain why results differ from predictions in a short experiment.
Before class
Do the Run board first. Students need Sample spaces and probability.
The one idea: expected count = probability × trials; observed counts vary around it. The common mistake is expecting the predicted count exactly, and calling a fair device unfair after a short experiment; it is planted in Noah's reasoning.
If you have real dice or coins, run the 60-roll experiment physically first and pool the class's counts; the board then lets students run far more trials than a lesson allows.
Running the lesson
Predict: take a show of hands; ask students who chose 'exactly 6' what 6 is.
Run: collect everyone's count of sixes on the board as a dot plot; ask how many got exactly 10.
Investigate: link relative frequency to Fractions, decimals and percentages.
Modify: before the two-students question, ask what range of heads in 10 flips is normal.
Make: ask for the general rule: trials = expected count ÷ probability.
When students get stuck
A student expects the predicted count exactly (Noah's mistake). Ask: Look at the class's counts. Did everyone get 10? Fix: Expected means 'about, on average', not every time.
A student gives the probability as the expected count. Ask: Out of how many trials? Fix: Multiply the probability by the number of trials.
Stretch and support
Stretch: Each of 30 students rolls a dice 60 times. Predict roughly how many of them will get exactly 10 sixes. Then simulate it with the board (about 1 in 7).
Support: Use the board's Expected count column to check each prediction.
Where it leads
Next: Many trials (AC9M7P02 node 2): what happens to the relative frequency over hundreds and thousands of trials.
Where it leads: simulating compound events (Year 8) and statistical significance much later.
What each step is for
how many sixes?: Committing to the number of sixes in 60 rolls brings out the expected count, and whether they expect it to happen exactly.
roll 60 times: Running 60 rolls and comparing the count of sixes with 10 shows that the expected count is a good guide, not a promise.
expected and observed: Expected count = probability × trials; the observed count varies around it, and the relative frequency is count ÷ trials. Noah's mistake treats a small difference in a short experiment as proof the dice is unfair.
one change at a time: One change at a time: a coin on the board, an unequal spinner, more trials, comparing two results, then the edge case of an expected count that is not a whole number.
expected counts: Expected counts and relative frequencies in new contexts, mixed; the expect-exactly slip planted again; the review keeps sample spaces fresh.
plan an experiment: Choosing the number of trials for a target expected count reverses the lesson: trials = expected count ÷ probability.
Now you can
Predict how often an outcome should happen in a number of trials.
Run an experiment, record counts and work out relative frequencies.
Explain why results differ from predictions in a short experiment.