Introduction to Binomial Model Statistics

Introduction to Binomial Model Statistics

           A binomial random variable be the number of success x in n frequent trials of a binomial experiment. The probability distribution of a binomial random variable is calling a binomial distribution. This is also recognized as a Bernoulli distribution).

` sum_(x=0)^nP(x=x)=sum_(x=0)^n(nC_(x)p^(x)q^(n-x)) ` . 

Where x- number of successes that answer as of the binomial testing.

             n- Number of trials during the binomial testing.

             P- Probability of success on an individual trial.

             q-   Probability of failure on an individual trial. (equal to 1 - P.)

Properties for Binomial Model Statistics

The testing consists of n repetitive trials.
Every one trial is able to result in just two possible outcomes. We describe one of these outcomes a success in addition to the other, a failure.
The probability of success, denote by P, is the identical on every trial.
The trials be independent so as to is, the result on one trial do not change the result on other trials.
Problems for Binomial Model Statistics

Problem 1 for Binomial Model Statistics

        6 cards are drawn successively with alternate from well shuffle deck of 52 cards. What is the probability that

               i)  all the six cards are spades

               ii) only 3 cards are spades

              iii) none is a spade.