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What should a sigma-algebra contain when the sample space is finite or countable?

When the sample space Ω\Omega is finite or countable, a suitable sigma-algebra should typically contain all singletons, meaning sets of the form {x}\{x\} for every x∈Ωx \in \Omega. This allows probabilities to be assigned to all individual outcomes.

Conditions

  • Ω\Omega is finite or countable.
  • The goal is to assign probabilities to individual outcomes.

Reasoning, step by step

  1. Identify that the sample space Ω\Omega is discrete (finite or countable).
  2. Recognize the desire to measure individual outcomes.
  3. Require that every singleton set {x}\{x\} belongs to the sigma-algebra F\mathcal{F}.
  4. Conclude that the smallest sigma-algebra containing all singletons in this case is the power set P(Ω)\mathcal{P}(\Omega).
  5. Verify that P(Ω)\mathcal{P}(\Omega) allows probabilities to be assigned to any subset of outcomes.

Example

For rolling a standard die, Ω={1,2,3,4,5,6}\Omega = \{1, 2, 3, 4, 5, 6\}. A suitable sigma-algebra should contain all singletons like {1}\{1\}, {2}\{2\}, etc., which means using the power set P(Ω)\mathcal{P}(\Omega).

Common misconceptions

  • Assuming that a sigma-algebra on a discrete space must be strictly smaller than the power set.
  • Thinking that only large composite events need to be measurable, ignoring individual outcomes.

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