a quantity expressed as a sum or difference of two terms relating to binomials; "binomial expression" consisting of two names or terms; "binomial nomenclature
Having two names; used of the system by which every animal and plant receives two names, the one indicating the genus, the other the species, to which it belongs
a mathematical expression that has two parts connected by the sign + or the sign -, for example 3x + 4y or x - 7 (binomium, from binominis, from bi- ( BI-) + nomen )
The discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p
The scientific system of naming each species of organism with a Latinized name in two parts; the first is the genus, and is written with an initial capital letter; the second is some specific epithet that distinguishes the species within the genus. By convention, the whole name is typeset in italics. The genus part is often abbreviated to its initial letter e.g. H. sapiens for Homo sapiens
A formula giving the expansion of a binomial such as ( a + b ) raised to any positive integer power, i.e. ( a + b )^{n} . It's possible to expand the power into a sum of terms of the form ax^{b}y^{c} where the coefficient of each term is a positive integer. For example:
(İstatistik) In probability theory and statistics, the binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. Such a success/failure experiment is also called a Bernoulli experiment or Bernoulli trial. In fact, when n = 1, the binomial distribution is a Bernoulli distribution. The binomial distribution is the basis for the popular binomial test of statistical significance
In statistics, the probability of finding exactly k successes in n independent Bernoulli trials, when each trial has success probability p: n k n-k P(k,n,p) = ( ) p (1-p) k This ideal distribution is produced by evaluating the probability function for all possible k, from 0 to n If we have an experiment which we think should produce a binomial distribution, and then repeatedly and systematically find very improbable test values, we may choose to reject the null hypothesis that the experimental distribution is in fact binomial Also see the binomial section of the Ciphers By Ritter / JavaScript computation pages
The distribution of the probability of a specified number of successes in a given number of independent trials, in each of which the probability of success is the same Useful in performing certain statistical significance tests on dichotomous data
The probability of exactly k independent events each with a probability p in M trials is M choose k pk (1-p)M-k, where M choose k = M!/(k! (M-k)!) The mean of the Binomial distribution is pM and its variance is p(1-p)M
The probability distribution describing the number of events (e g , heads for coin flips) in a given number of trials for a specified probability of the event happening on each trial
A random variable has a binomial distribution (with parameters n and p) if it is the number of "successes" in a fixed number n of independent random trials, all of which have the same probability p of resulting in "success " Under these assumptions, the probability of k successes (and n-k failures) is nCk pk(1-p)n-k, where nCk is the number of combinations of n objects taken k at a time: nCk = n!/(k!(n-k)!) The expected value of a random variable with the Binomial distribution is n×p, and the standard error of a random variable with the Binomial distribution is (n×p×(1 - p))½ This page shows the probability histogram of the binomial distribution
Binomial distributions model (some) discrete random variables When a coin is flipped, the outcome is either a head or a tail ie there are two mutually exclusive possible outcomes For convenience, one of the outcomes can be termed 'success' and the other outcome termed 'failure' If a coin is flipped N times, then the binomial distribution can be used to determine the probability of obtaining exactly r successes in the N outcomes The formula that is used assumes that the events: fall into only two categories (ie are dichotomous); are mutually exclusive; are independent and are randomly selected
The frequency distribution of the probability of a specified number of successes in an arbitrary number of repeated independent Bernoulli trials. Also called Bernoulli distribution
The probability model for the number of successes x in a fixed number n of two-outcome ("success," "failure") trials that are independent and are of equal probability p; the distribution is computed as
A calculation that measures the likelihood of events taking place where the probability is measured between 0 (the event will certainly not occur) and 1 (the event is absolutely certain)
"A statistical distribution giving the probability of obtaining a specific number of successes in a binomial experiment" (Borwein, Watters, & Borowski, 1997)
In probability, a binomial distribution gives the probabilities of k outcomes A (or n-k outcomes B) in n independent trials for a two-outcome experiment in which the possible outcomes are denoted A and B
A distribution which gives the probability of observing X successes in a fixed number (n) of independent Bernoulli trials p represents the probability of a success on a single trial Parameters: event probability 0<=p<=1 number of trials: n>0 Domain: X=0,1, ,n Mean: np Variance: np(1-p)
The scientific naming of species whereby each species receives a Latin or Latinized name of two parts, the first indicating the genus and the second being the specific epithet. For example, Juglans regia is the English walnut; Juglans nigra, the black walnut. System of naming organisms in which each organism is indicated by two words, the genus (capitalized) and species (lowercase) names, both written in italics. For example, the tea rose is Rosa odorata; the common horse is Equus caballus. The system was developed by Carolus Linnaeus in the mid 18th century. The number of binomial names proliferated as new species were established and more categories were formed, and by the late 19th century the nomenclature of many groups of organisms was confused. International committees in the fields of zoology, botany, bacteriology, and virology have since established rules to clarify the situation. See also taxonomy
The theorem that specifies the expansion of any power (a + b). In algebra, a formula for expansion of the binomial (x + y) raised to any positive integer power. A simple case is the expansion of (x + y)^2, which is x^2 + 2xy + y^2. In general, the expression (x + y)^n expands to the sum of (n + 1)terms in which the power of x decreases from n to 0 while the power of y increases from 0 to n in successive terms. The terms can be represented in factorial notation by the expression [n!/((n -r)!r!)]x^n -ry^r in which r takes on integer values from 0 to n