Binomial distribution and P-value

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Binomial distribution and P-value

Binomial distribution vs. P-value

In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own boolean-valued outcome: a random variable containing a single bit of information: success/yes/true/one (with probability p) or failure/no/false/zero (with probability q. In statistical hypothesis testing, the p-value or probability value or asymptotic significance is the probability for a given statistical model that, when the null hypothesis is true, the statistical summary (such as the sample mean difference between two compared groups) would be the same as or of greater magnitude than the actual observed results.

Binomial coefficient

In mathematics, any of the positive integers that occurs as a coefficient in the binomial theorem is a binomial coefficient.

Binomial coefficient and Binomial distribution · Binomial coefficient and P-value · See more »

Central limit theorem

In probability theory, the central limit theorem (CLT) establishes that, in some situations, when independent random variables are added, their properly normalized sum tends toward a normal distribution (informally a "bell curve") even if the original variables themselves are not normally distributed.

Binomial distribution and Central limit theorem · Central limit theorem and P-value · See more »

Cumulative distribution function

In probability theory and statistics, the cumulative distribution function (CDF, also cumulative density function) of a real-valued random variable X, or just distribution function of X, evaluated at x, is the probability that X will take a value less than or equal to x. In the case of a continuous distribution, it gives the area under the probability density function from minus infinity to x. Cumulative distribution functions are also used to specify the distribution of multivariate random variables.

Binomial distribution and Cumulative distribution function · Cumulative distribution function and P-value · See more »

Fair coin

In probability theory and statistics, a sequence of independent Bernoulli trials with probability 1/2 of success on each trial is metaphorically called a fair coin.

Binomial distribution and Fair coin · Fair coin and P-value · See more »

Normal distribution

In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.

Binomial distribution and Normal distribution · Normal distribution and P-value · See more »

Probability distribution

In probability theory and statistics, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment.

Binomial distribution and Probability distribution · P-value and Probability distribution · See more »

Random variable

In probability and statistics, a random variable, random quantity, aleatory variable, or stochastic variable is a variable whose possible values are outcomes of a random phenomenon.

Binomial distribution and Random variable · P-value and Random variable · See more »

Statistical hypothesis testing

A statistical hypothesis, sometimes called confirmatory data analysis, is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.

Binomial distribution and Statistical hypothesis testing · P-value and Statistical hypothesis testing · See more »

Statistical significance

In statistical hypothesis testing, a result has statistical significance when it is very unlikely to have occurred given the null hypothesis.

Binomial distribution and Statistical significance · P-value and Statistical significance · See more »

Variance

In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its mean.

Binomial distribution and Variance · P-value and Variance · See more »