Difference between revisions of "Dictionary:Conditional probability/es"

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La probabilidad de "E" si "C"_i ya ha ocurrido está dado por $P(E|C_{i})$ .

El teorema de Bayes da la probabilidad a posteriori:

P(C_{i}|E)={\frac {P(C_{i})P(E|C_{i})}{\sum P(C_{j})P(E|C_{j})}}

,

where P(C_i)=a priori probability of C_i

@@ Line 4: / Line 4: @@
 La probabilidad de "E" si "C"<sub>''i''</sub> ya ha ocurrido está dado por <math>P(E|C_i) </math>. <b>
-Bayes's theorem</b> gives the a posteria probability:
+El teorema de Bayes</b> da la probabilidad a posteriori:
 <center><math>P(C_i|E)=\frac{P(C_i)P(E|C_i)}{\sum P(C_j) P(E|C_j)}</math>,</center>
 where ''P''(''C''<sub>''i''</sub>)=a priori probability of ''C''<sub>''i''</sub>