ผลต่างระหว่างรุ่นของ "Probstat/notes/basic"
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แถว 8: | แถว 8: | ||
== Probability axioms == | == Probability axioms == | ||
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+ | We would like to assign probabilities to events. Let ''S'' denote the sample space. Formally a function ''P'' is a probability function if it satisfies the follow 3 axioms. | ||
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+ | '''1:''' For any event ''E'', <math>0\leq P(E)\leq 1</math>. | ||
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+ | '''2:''' <math>P(S)=1</math>. | ||
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+ | '''3:''' For any countable sequence of mutually exclusive events <math>E_1,E_2,\ldots</math>, we have that | ||
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+ | <math>P(\bigcup_i E_i) = \sum_i P(E_i)</math>. | ||
== Useful properties == | == Useful properties == |
รุ่นแก้ไขเมื่อ 03:33, 13 กันยายน 2557
- This is part of probstat. These notes are meant to be used in complement to the video lectures. They only contain summary of the materials discussed in the video. Don't use them to avoid watching the clips please.
Random experiments
When we would like to talk about probability, we shall start with a random experiment. After we perform this experiment we get an outcome. The set of all possible outcomes is called a sample space, usually denoted by S.
We are generally interested in outcomes with certain properties, usually referred to as an event. Formally, an event is a subset of the sample space S.
Probability axioms
We would like to assign probabilities to events. Let S denote the sample space. Formally a function P is a probability function if it satisfies the follow 3 axioms.
1: For any event E, .
2: .
3: For any countable sequence of mutually exclusive events , we have that
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