# Strategy for Information Markets/Information Cascades

## Conditional Probability[edit | edit source]

If **"Probability of A given B"** or **"Probability of A conditioned on B"**

then,

### Bayes' Rule[edit | edit source]

## Condorcet Jury Theorem[edit | edit source]

### Binomial Distribution[edit | edit source]

If the probability of one success is , then

while

- stands for the probability of a particular trial being a success

- stands for the probability of a particular trial being a failure

and in math,

### Group Decision/Voting[edit | edit source]

In order to determine if a group decision/voting is correct, the number of successes needs to be more than half of . The following formula derived from the Binomial Distribution Function tells the chance of the right group decision.

In the case here, by eliminating the situation that the vote is a tie, let's assume that the number of votes is odd so that could be more than half of .

Therefore,

### Influence-Dependent Model of Group Decision/Voting[edit | edit source]

In daily lives, people usually make votes with other influences, instead of absolutely independent decision making. Let's derive another model to determine the probability of correct group decision on other influences.

Let

- the probability of being correct

- the group makes the correct decision (more than half of the votes are correct)

- the probability of the influence being correct

- the probability of the voter following the influence to make decision

- the probability of the voter being correct if the influence is correct

- the probability of the voter being correct if the influence is wrong

Therefore,

## Central Limit Theorem[edit | edit source]

Let be a series of independently and identically distributed random variables. The mean of these variables is and the variance is .

Let .

When gets larger, gets closer to be a random variable that is normally distributed and has mean and variance