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Marginal Probability
Probability of event A happening, denoted by P(A), is called single probability, marginal or unconditional probability.
Marginal or Unconditional Probability is defined as the ratio of number of possible outcomes favorable to the event A to the total number of possible outcomes.
P(A)
The definition assumes that the elements of the sample space have an equally likely chance of occurring.
Example
A gambler places a bet on numbers 14 through 25. There are 12 equally likely winning outcomes. The roulette wheel (a gambling instrument which can display any one of 38 equally likely numbers as the winning number) contains 38 equally likely outcomes.
The probability of the wheel stopping on a number from 14 through 25 (say event A) = 12/38 = 0.316.
The probability of losing, i.e. the wheel stopping on numbers other than 14 through 25 (say event B) is the probability of the complement of A occurring. The complement of an event A is defined as A' , where A' represents the non-occurrence of event A. So, the probability of A' (B) = 26/38 = 0.684.
P (A') = P(B) = 1 - P(A) because A and A' are the only possible events and they are mutually exclusive events of the sample of 38 equally likely outcomes. Thus, P(A) + P (A') = 1 and P(A and A' ) is 0.
Non Linear Relationships If the correlation coefficient and the scatter diagram do not indicate linear relationship, then the relationship may be nonlinear. Two such relations
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