Simple probability experiments connect a chance situation to its possible outcomes and predictions about which outcomes are more, less, or equally likely; when outcomes are equally likely, likelihood can be represented with simple fractions. Tallying results over repeated trials and comparing experimental frequencies with predictions develops understanding that random results vary, while larger sets of trials often better reflect expected likelihood. Formal probability rules, dependent or compound events, and advanced statistical analysis are beyond this understanding.
A probability experiment is a chance activity that you repeat to see what happens.
To conduct one:
Example: Tossing a coin
A coin can land on:
If the coin is fair, heads and tails are equally likely. There are equally likely outcomes, so the predicted chance of heads is
and the predicted chance of tails is also
Now toss the coin times. Suppose the results are:
| Result | Tally | Number |
|---|---|---|
| Heads | $| | |
| Tails | $| | $ |
The experiment produced heads and tails. Heads occurred more often in these tosses, but that does not mean heads are more likely. The results changed because each toss is random.
The prediction was about equal numbers of heads and tails. This experiment was not exactly equal, but it could become closer to the prediction if the coin were tossed many more times. For example, in tosses, we might expect the numbers of heads and tails to be closer to each, although they still might not be exactly equal.
Random results can vary, but larger numbers of trials often give results that are closer to the expected likelihood.
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