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During 2006 in U.S.A there were 4,265,555 live births. Male births were 2,184,237 and 2,081,318 were female births. The probability that a new baby born would be female is p(x=f). Where f represent female

Number of female /Total number of birth   = 2,081,318/4,265,555      = 0.4879                                                       

In 1990 there were 4,158,212 live births in US out of which 1,976,198 were female. Hence, the probability that a baby born will be a female is

1976198/4158212 =0.4753                               

from the two examples above, we can observe that the probability that a female baby will be born increases overtime.

Probability distributions measures what will probably happen. From a given known information we can be able to approximate the probability of occurrence of a certain event.

Under the probability we use probability to show how the entire set of event of an experiment can easily be presented and expressed as random variables. Suppose you toss a coin. The outcomme can be either a head or a tail. The probability of a getting a head is ½.

A probability distribution display all possible outcomes of an experiment and the probability associated with each outcome. Probability distribution is applied in real life situations. From the above cited examples, we can draw a hypothetical probability distribution table as shown below.

The above table shows the distribution of births in the two years 1990 and 2006. Column total number of births represents the sum of female and male births. To obtain the probability of female births, we use the function p(x=f). Where f represent female

P(x=f) = Number of female /Total number of births.

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