A tree diagram represents the sample space of a finite, multi-step random experiment, with branches showing possible results at each stage and each complete path from the start to an endpoint representing one ordered outcome. The diagram makes clear whether outcomes are exhaustive and nonoverlapping, supports grouping paths into events, and provides a structure for assigning or calculating probabilities. The focus is on simple experiments with a few stages, not generalized combinatorial notation or large, highly dependent sample spaces.
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A tree diagram shows the stages of a random experiment from left to right. Each branch shows one possible result, and each complete path from the start to the end represents one outcome.
Example: A fair coin is tossed twice. Find the sample space and the probability of getting exactly one head.
Step 1: Identify the stages.
There are two stages:
For each toss, the possible results are (heads) and (tails).
Step 2: Draw branches for the first toss.
From the starting point, draw one branch for and one branch for .
Step 3: Continue each branch for the second toss.
Each first-toss result can be followed by either or .
Start
├── H
│ ├── H → HH
│ └── T → HT
└── T
├── H → TH
└── T → TT
Step 4: List the complete paths.
The sample space is
Each two-letter result is one ordered outcome. For example, means heads first and tails second, while means tails first and heads second. They are different outcomes because the order is different.
The paths are exhaustive because they include every possible result. They are nonoverlapping because one toss sequence cannot be both and .
Step 5: Use the tree to find an event.
Exactly one head occurs on the paths
Because the coin is fair, each branch has probability . Therefore, each complete path has probability
There are two paths with exactly one head, so
To make a tree diagram, show every possible result at each stage, follow every branch to an endpoint, and use the complete paths as the outcomes in the sample space.
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