Correlation and condjtional probabilty

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In summary, correlation is a statistical measure that shows the strength and direction of the relationship between two variables and is measured using a correlation coefficient. It is different from causation, as correlation does not imply causation. Conditional probability is the probability of an event occurring given that another event has already occurred. It is related to correlation, as it can help us understand the relationship between two variables. While correlation and conditional probability can inform predictions, they cannot guarantee accurate predictions as other factors should also be considered.
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koustubh25
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Hello,
I have just started learning these things, would really appreciate any help on this.
There are 4 nodes in a network (say A,B,C,D)and each node has certain failure probabilities( P(af),P(bf),P(cf),P(df) ).
Then,I have this 4x4 correlation Matrix which contains the correlation coefficients for every pair of nodes.
How can I calculate P(af|bf cf df)?

Thanks
 
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1. What is correlation and how is it measured?

Correlation is a statistical measure that shows the strength and direction of the relationship between two variables. It is measured using a correlation coefficient, with values ranging from -1 to 1. A positive correlation means that the two variables increase or decrease together, while a negative correlation means that as one variable increases, the other decreases.

2. How is correlation different from causation?

Correlation does not imply causation. Just because two variables are correlated does not mean that one causes the other. There could be other underlying factors or a third variable that is responsible for the observed relationship between the two variables.

3. What is conditional probability?

Conditional probability is the probability of an event occurring given that another event has already occurred. It is often denoted as P(A|B), where A is the event of interest and B is the condition.

4. How is conditional probability related to correlation?

Conditional probability can help us understand the relationship between two variables by considering the probability of one variable given the other. For example, if the conditional probability of event A given event B is high, it could indicate a positive correlation between the two variables.

5. Can correlation and conditional probability be used to make predictions?

Correlation and conditional probability can provide valuable insights and help inform predictions, but they cannot guarantee accurate predictions. Other factors and variables should also be considered in making predictions.

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