Does the number of events in a set always sum to one?

In summary, the probability of selecting a single letter from \(\{A, B, C\}\) is \(\frac{1}{3}\) and the probability of all events sums to \(1\). However, the question is asking about power sets and the total number of events being \(2^n\), where \(n\) is the number of simple events. This is the number of power sets, which may not make sense to sum. The inclusion-exclusion principle can be used to calculate the probability of selecting all possible events, but the question remains unclear and may need further clarification from a professor.
  • #1
Dustinsfl
2,281
5
If a single letter is selected at random from \(\{A, B, C\}\), find the probability of all events. Recall that the total number of events is \(2^n\), where \(n\) is the number of simple events. Do these probabilities sum to one? If not, why not?

This question comes verbatim from a book on probability and random process.

The probability of selecting a single letter is \(\frac{1}{3}\) and the probability of all events sums to \(1\). However, the question is then askig about power sets since it says recall that the total number of events is \(2^n\). This is the number of power sets. Aren't there only three events? Does it even make sense to sum power sets?
 
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  • #2
dwsmith said:
If a single letter is selected at random from \(\{A, B, C\}\), find the probability of all events. Recall that the total number of events is \(2^n\), where \(n\) is the number of simple events. Do these probabilities sum to one? If not, why not?

This question comes verbatim from a book on probability and random process.

The probability of selecting a single letter is \(\frac{1}{3}\) and the probability of all events sums to \(1\). However, the question is then askig about power sets since it says recall that the total number of events is \(2^n\). This is the number of power sets. Aren't there only three events? Does it even make sense to sum power sets?

$A$ or $B$ is an event ,.,,
 
  • #3
zzephod said:
$A$ or $B$ is an event ,.,,

Both A and B are events as well as C.
 
  • #4
I can't really see the motivation of this question, especially with the restriction that only one letter may be chosen. If we can ignore that restriction for a moment, then it seems more pertinent as $P[A \cup B \cup C]=1$ and that calculation will involve all subsets of $\{A,B,C \}$. As you know though, this will not simply be a sum of all possible events because we need to subtract some events due to double counting. So if we add these together, this will be greater than 1.

How the above applies to choosing just one letter at a time though, that I can't say. Even so, here's my two cents.
 
  • #5
dwsmith said:
Both A and B are events as well as C.

I shall make things more explicit since a discreet prod is not sufficient: $\{A\}$, $\{B\}$ and $\{C\}$ are simple events and $(\{A\} \lor \{B\})$ is an event as is ...

.
 
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  • #6
Jameson said:
I can't really see the motivation of this question, especially with the restriction that only one letter may be chosen. If we can ignore that restriction for a moment, then it seems more pertinent as $P[A \cup B \cup C]=1$ and that calculation will involve all subsets of $\{A,B,C \}$. As you know though, this will not simply be a sum of all possible events because we need to subtract some events due to double counting. So if we add these together, this will be greater than 1.

How the above applies to choosing just one letter at a time though, that I can't say. Even so, here's my two cents.

zzephod said:
I shall make things more explicit since a discreet prod is not sufficient: $\{A\}$, $\{B\}$ and $\{C\}$ are simple events and $(\{A\} \lor \{B\})$ is an event as is ...

.

From these two post, I am inferring to use the Inclusion-Exclusion Principle; that is,
\[
P[A\cup B\cup C] = \sum P[E_i] - P[A\cap B] - P[B\cap C] - P[A\cap C] + P[A\cap B\cap C]
\]
where \(E_i\) is \(A\), \(B\), \(C\) for \(i = 1, 2, 3\)
 
  • #7
dwsmith said:
From these two post, I am inferring to use the Inclusion-Exclusion Principle; that is,
\[
P[A\cup B\cup C] = \sum P[E_i] - P[A\cap B] - P[B\cap C] - P[A\cap C] + P[A\cap B\cap C]
\]
where \(E_i\) is \(A\), \(B\), \(C\) for \(i = 1, 2, 3\)

All of the probabilities on the right hand side, other that the first sum, are zero (read your own question).

.
 
  • #8
zzephod said:
All of the probabilities on the right hand side, other that the first sum, are zero (read your own question).

.

I am sorry, but I have no idea what the hints are trying to steer me towards or what the question wants.
 
  • #9
dwsmith said:
I am sorry, but I have no idea what the hints are trying to steer me towards or what the question wants.

I really think is a strange question and would ask my professor to clarify. It's clear you understand the inclusion-exclusion principle and understand the power set, but how they tie together in this problem is strange.

Maybe the goal is to write out all possible events - no events, 1 event, 2 events and all three then notice that the probability of no events, 2 events and 3 events are all 0 so if you sum these you do in fact get 1.
 
  • #10
dwsmith said:
I am sorry, but I have no idea what the hints are trying to steer me towards or what the question wants.

It was not a hint but a statement, read your own question, can $A$ and $B$ both be drawn. The answer is no, so $P(\{A\} \cap \{B \})=0$ similarly any other intersection of distinct results has zero probability.

.
 
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FAQ: Does the number of events in a set always sum to one?

What is the definition of probability?

Probability is a measure of the likelihood of an event occurring. It is expressed as a number between 0 and 1, where 0 represents impossibility and 1 represents certainty.

How is probability calculated?

Probability is calculated by dividing the number of favorable outcomes by the total number of possible outcomes. This is known as the classical or theoretical probability. Other methods of calculating probability include empirical (based on past data) and subjective (based on personal judgment) approaches.

What is the difference between theoretical and experimental probability?

Theoretical probability is based on the assumption of equally likely outcomes, while experimental probability is based on actual observations or experiments. Theoretical probability is used to predict the likelihood of an event, while experimental probability is used to analyze the results of an experiment or real-life situation.

How does probability relate to statistics?

Probability is a fundamental concept in statistics, as it is used to make predictions and draw conclusions about a population based on a sample. Probability is also used to determine the likelihood of a certain outcome in statistical tests and analysis.

What is the role of probability in decision-making?

Probability can be used to make informed decisions by assessing the likelihood of different outcomes. It helps to weigh the potential risks and benefits of a decision and provides a framework for evaluating different options. Probability can also be used to make predictions about future events, which can inform decision-making processes.

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