Tags: #◇Computer Science #◇STT101A #◇Conceptual #◇Partition of Sample Space
◇Overview
A Partition of a Sample Space is a collection of non-empty events that divides into non-overlapping regions covering the entire space. Every elementary outcome belongs to one and only one event in the partition.
◇Key Definitions
A collection of events forms a partition of if and only if it satisfies two conditions simultaneously:
- Pairwise Mutually Exclusive (Disjoint): for all .
- Collectively Exhaustive: (which implies ).
- Decomposition of Any Event : Any event is partitioned into disjoint pieces , which is the foundation of the Law of Total Probability and Bayes' Theorem.
◇Worked Example
Problem: For rolling a six-sided die with , verify which of the following collections is a valid partition of :
- : Valid (disjoint and union is ).
- : Invalid (not disjoint, since is in both).
- : Invalid (not exhaustive, since and are missing).
◇References & Navigation
- Previous Topic: ◇Contingency Table
- Next Topic: ◇Total Probability Rule
- Related Notes: ◇Bayes's Rules, ◇Independent Events
ACTIVE RECALL VERIFICATION
Select an answer to verify conceptual comprehension and reveal the technical rationale.
Which two conditions are jointly required for a collection of events to form a partition of sample space ?
For any event (with and ), what is the simplest two-set partition of generated by ?
If is a partition of with and , what must equal?
Why does a partition allow us to write for any event ?
Let . Why does the collection fail to be a partition of ?