{"id":3969,"date":"2021-08-11T14:38:14","date_gmt":"2021-08-11T14:38:14","guid":{"rendered":"https:\/\/mathemerize.com\/?p=3969"},"modified":"2021-11-27T23:13:41","modified_gmt":"2021-11-27T17:43:41","slug":"formula-for-binomial-probability-distribution","status":"publish","type":"post","link":"https:\/\/mathemerize.com\/formula-for-binomial-probability-distribution\/","title":{"rendered":"Formula for Binomial Probability Distribution"},"content":{"rendered":"
Here, you will learn formula for binomial probability distribution in probability with example.<\/p>\n
Let’s begin –<\/p>\n
Suppose that we have an experiment such as tossing a coin or die repeatedly or choosing a marble from an urn repeatedly. Each toss or selection is called a trial. In any single trial there will be a probability associated with a particular event such as head on the coin, 4 on the die, or selection of a red marble. In some cases this probability will not change from one trial to the next(as in tossing a coin or die). Such trials are then said to be independent and are often called Bernoulli trials after James Bernoulli who investigated them at the end of the seventeenth century.<\/p>\n
Let p be the probability that an event will happen in any single Bernoulli trial(called the probability of success).Then q = 1 – p is the probability that the event will fail to happen in any single trial (called the probability of Failure). The probability that the event will happen exactly x times in n trials (i.e., x success and n – x failures will occur) is given by the probability function.<\/p>\n
\nf(x) = P(X = x) = \\(\\binom{n}{x} p^x q^{n-x}\\) = \\(n!\\over {x!(n – x)!}\\) \\(p^xq^{n-x}\\)<\/p>\n<\/blockquote>\n
where the random variable X denotes the number of success in n trials and x = 0, 1,…….,n.<\/p>\n\n\n
Example : <\/span>What is the probability of getting exactly 2 heads in 6 tosses of a fair coin? <\/p>\n
Solution : <\/span>The probability of getting exactly 2 heads in 6 tosses of a fair coin is
\n \t\t P(X = 2) = \\(\\binom{6}{2} ({1\\over 2})^2 ({1\\over 2})^{6-2}\\)
\n= \\(6!\\over {2!4!}\\) \\(({1\\over 2})^2 ({1\\over 2})^{6-2}\\)
\n= \\({15}\\over{64}\\)
<\/p>\n\n\nThe discrete probability function is often called the binomial distribution since for x = 0, 1, 2,……,n, it corresponds to successive terms in the binomial expansion.<\/p>\n
\\((q + p)^n\\) = \\(q^n\\) + \\(\\binom{n}{1} p q^{n-1}\\) + \\(\\binom{n}{2} p^2 q^{n-2}\\) + ……….+ \\(p^n\\) = \\({\\sum_{n=1}^{\\infty}}\\)\\(\\binom{n}{x} p^x q^{n-x}\\)<\/p>\n\n\n