Last modified: September 21, 2024
This article is written in: πΊπΈ
Probability Trees
Probability trees are a visual representation of all possible outcomes of a probabilistic experiment and the paths leading to these outcomes. They are especially helpful in understanding sequences of events, particularly when these events are conditional on previous outcomes.
Structure of Probability Trees
A probability tree starts with a root node that branches out into possible outcomes of the first event. Each of these outcomes becomes a node that branches into further outcomes, continuing for as many events as are being considered. The branches are labeled with probabilities, and the path to each outcome shows the sequence of events leading to that outcome.
Rules for Probability Trees
 The sum of the probabilities of all branches from a single node must equal 1, as they represent all possible outcomes of that event.
 The probability of an event or sequence of events represented by a path is found by multiplying the probabilities along the path.
 The probability of an event that can occur in multiple ways is the sum of the probabilities of all paths leading to that event.
Example: Drawing Cards
Consider a simplified example where we draw one card from a standard deck of 52 cards, and we're interested in the event of drawing a heart or not drawing a heart. The event space for this problem can be represented using a probability tree, which helps visualize the possible outcomes and their associated probabilities.
Tree:
__Heart (1/4)

Initial βββ€

__Not Heart (3/4)
Here is a stepbystep explanation of the tree:
 The initial node represents the state before any card is drawn.
 From the initial node, there are two possible outcomes: drawing a heart or not drawing a heart.
 The probability of drawing a heart is determined by the number of hearts in the deck (13) divided by the total number of cards (52). Thus, the probability of drawing a heart is:
$$ P(\text{Heart}) = \frac{13}{52} = \frac{1}{4} $$
 The probability of not drawing a heart is simply the complement of the probability of drawing a heart. Since there are 39 cards that are not hearts in a standard deck of 52 cards, the probability of not drawing a heart is:
$$ P(\text{Not Heart}) = \frac{39}{52} = \frac{3}{4} $$
This structure is consistent with the principle that the total probability of all possible outcomes must sum to 1, i.e.:
$$ P(\text{Heart}) + P(\text{Not Heart}) = 1 $$
$$ \frac{1}{4} + \frac{3}{4} = 1 $$
Thus, the probability tree correctly reflects the outcomes and their associated probabilities.
Example: Tossing a Coin and Rolling a Die
In this example, we examine two independent events: first, tossing a coin, and then rolling a die. The probability tree for this scenario helps to visualize the sequential outcomes and probabilities at each stage of the experiment.
Tree:
__Head (1/2)βββ1 (1/6)
 .
 .
Initial βββ€ 6 (1/6)

__Tail (1/2)βββ1 (1/6)
.
.
6 (1/6)
Interpreting the Probability Tree
I. Initial Node (Coin Toss): The experiment begins with a coin toss. The initial node represents the state before any action is taken.
II. First Level Branches (Coin Toss):
 The first branching represents the two possible outcomes of tossing a fair coin: "Head" and "Tail."
 The probability of getting a "Head" is:
$$ P(\text{Head}) = \frac{1}{2} $$
Similarly, the probability of getting a "Tail" is:
$$ P(\text{Tail}) = \frac{1}{2} $$
These probabilities reflect the equal likelihood of both outcomes for a fair coin.
III. Second Level Branches (Die Roll):
 After the coin toss, we roll a fair sixsided die.
 Each outcome of the die roll (the numbers 1 through 6) is represented by the second level of branches.
 The probability of rolling any specific number on the die (e.g., rolling a 1, 2, or 6) is:
$$ P(\text{Die Roll}) = \frac{1}{6} $$
since each face of the die is equally likely to appear.
Calculating Probabilities of Combined Events
The probability of any combined outcome (e.g., tossing a "Head" followed by rolling a "4") is calculated by multiplying the probabilities of the individual events along the relevant path in the tree. For example:
$$ P(\text{Head and 4}) = P(\text{Head}) \times P(4) = \frac{1}{2} \times \frac{1}{6} = \frac{1}{12} $$
Similarly, the probability of getting a "Tail" followed by rolling a "2" would be:
$$ P(\text{Tail and 2}) = P(\text{Tail}) \times P(2) = \frac{1}{2} \times \frac{1}{6} = \frac{1}{12} $$
General Form
The total probability for any combined event is always the product of the individual probabilities along its branch. Since the events are independent, the combined probability of any outcome from the coin toss followed by a die roll is given by:
$$ P(\text{Combined Event}) = P(\text{Coin Outcome}) \times P(\text{Die Outcome}) $$
The probability tree can be used to calculate all possible combinations of outcomes, and since there are 12 possible combinations (2 coin outcomes Γ 6 die outcomes), the total probabilities sum to 1. This ensures that the model accounts for all potential outcomes:
$$ \sum P(\text{Outcome}) = 1 $$
Example: Rolling Two Dice
In this example, we explore the scenario of rolling two sixsided dice simultaneously. A probability tree provides a clear visualization of all possible outcomes and their associated probabilities.
Tree:
_____1 (1/6)ββ1 (1/6)
 .
 .
 6 (1/6)

_____2 (1/6)ββ1 (1/6)
Initial βββ€ .
 .
 6 (1/6)

__ ... (1/6)ββ1 (1/6)
 .
 .
 6 (1/6)

_____6 (1/6)ββ1 (1/6)
.
.
6 (1/6)
Interpreting the Probability Tree
I. Initial Node (Before Rolling Dice): The initial node represents the state before any dice are rolled.
II. First Level Branches (First Die Roll):
 Each branch from the initial node corresponds to one of the six possible outcomes from rolling the first die, which are the numbers 1 through 6.
 Since the die is fair, the probability of any outcome on the first die is:
$$ P(\text{First Die Outcome}) = \frac{1}{6} $$
III. Second Level Branches (Second Die Roll):
 After rolling the first die, for each outcome, there are six branches representing the possible outcomes of rolling the second die.
 Each outcome on the second die (also numbered 1 through 6) has an equal probability of occurring, independent of the first die's outcome:
$$ P(\text{Second Die Outcome}) = \frac{1}{6} $$
Calculating Probabilities of Combined Events
To compute the probability of rolling a specific combination (e.g., rolling a "3" on the first die and a "5" on the second), we multiply the probabilities along the path that represents the combined event. For example:
$$ P(3 \text{ on first die and } 5 \text{ on second die}) = P(3) \times P(5) = \frac{1}{6} \times \frac{1}{6} = \frac{1}{36} $$
Since the outcomes of the two dice are independent, the probability of any specific combination is always the product of the probabilities of the individual outcomes.
Total Number of Outcomes
There are 36 possible combinations of outcomes (6 outcomes from the first die Γ 6 outcomes from the second die). Each combination has an equal probability of occurring:
$$ P(\text{Any Specific Combination}) = \frac{1}{36} $$
General Form
The probability of rolling any specific pair of numbers (e.g., a "2" on the first die and a "6" on the second) is calculated using the formula:
$$ P(\text{First Die Outcome and Second Die Outcome}) = P(\text{First Die Outcome}) \times P(\text{Second Die Outcome}) = \frac{1}{6} \times \frac{1}{6} = \frac{1}{36} $$
Thus, the total probability of all possible outcomes from rolling two dice must sum to 1:
$$ \sum P(\text{Outcome}) = 1 $$
This ensures that the probability model is complete and accounts for every possible pair of outcomes from rolling two dice.
Example: Drawing Marbles from a Bag
Consider a scenario where a bag contains 6 red marbles (R) and 4 green marbles (G). Two marbles are drawn one after the other without replacement. We aim to calculate the probabilities of the following outcomes:
 P(R then G): Drawing a red marble followed by a green marble.
 P(G then R): Drawing a green marble followed by a red marble.
 P(both R): Drawing two red marbles.
 P(both G): Drawing two green marbles.
The following probability tree illustrates the outcomes and the conditional probabilities:
Tree:
βββ R (5/9)
βββ R (6/10)
β βββ G (4/9)
Initial Node
β βββ R (6/9)
βββ G (4/10)
βββ G (3/9)
Calculations
I. P(R then G) (Red marble followed by a Green marble):
The probability of drawing a red marble first is:
$$ P(\text{R first}) = \frac{6}{10} $$
Given that a red marble is drawn first, the probability of drawing a green marble second is:
$$ P(\text{G second  R first}) = \frac{4}{9} $$
Therefore, the probability of drawing a red marble followed by a green marble is:
$$ P(\text{R then G}) = P(\text{R first}) \times P(\text{G second  R first}) = \frac{6}{10} \times \frac{4}{9} = \frac{24}{90} \approx 0.267 $$
II. P(G then R) (Green marble followed by a Red marble):
The probability of drawing a green marble first is:
$$ P(\text{G first}) = \frac{4}{10} $$
Given that a green marble is drawn first, the probability of drawing a red marble second is:
$$ P(\text{R second  G first}) = \frac{6}{9} $$
Therefore, the probability of drawing a green marble followed by a red marble is:
$$ P(\text{G then R}) = P(\text{G first}) \times P(\text{R second  G first}) = \frac{4}{10} \times \frac{6}{9} = \frac{24}{90} \approx 0.267 $$
III. P(both R) (Both marbles are red):
The probability of drawing a red marble first is:
$$ P(\text{R first}) = \frac{6}{10} $$
After drawing one red marble, there are 5 red marbles left out of 9, so the probability of drawing a second red marble is:
$$ P(\text{R second  R first}) = \frac{5}{9} $$
Therefore, the probability of drawing two red marbles is:
$$ P(\text{both R}) = P(\text{R first}) \times P(\text{R second  R first}) = \frac{6}{10} \times \frac{5}{9} = \frac{30}{90} = 0.333 $$
IV. P(both G) (Both marbles are green):
The probability of drawing a green marble first is:
$$ P(\text{G first}) = \frac{4}{10} $$
After drawing one green marble, there are 3 green marbles left out of 9, so the probability of drawing a second green marble is:
$$ P(\text{G second  G first}) = \frac{3}{9} $$
Therefore, the probability of drawing two green marbles is:
$$ P(\text{both G}) = P(\text{G first}) \times P(\text{G second  G first}) = \frac{4}{10} \times \frac{3}{9} = \frac{12}{90} \approx 0.133 $$