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53 relations: Arithmetic mean, Binomial distribution, Burr distribution, Cauchy distribution, Chi-squared distribution, Confidence interval, CumFreq, Cumulative distribution function, Dagum distribution, Density estimation, Expected value, Exponential distribution, Forecasting, Fréchet distribution, Frequency (statistics), Gompertz distribution, Goodness of fit, Gumbel distribution, Histogram, Hydrology, Kurtosis, L-moment, Laplace distribution, Linear map, List of probability distributions, Log-logistic distribution, Log-normal distribution, Logistic distribution, Maximum likelihood estimation, Maximum spacing estimation, Mean, Method of moments (statistics), Mixture distribution, Mode (statistics), Normal distribution, Numerical method, Observational error, Parameter, Pareto distribution, Prediction, Probability, Probability density function, Probability distribution, Product distribution, Q–Q plot, Return period, Skewness, Standard deviation, Student's t-distribution, Survival function, ..., Uncertainty, Variance, Weibull distribution. Expand index (3 more) »
Arithmetic mean
In mathematics and statistics, the arithmetic mean (stress on third syllable of "arithmetic"), or simply the mean or average when the context is clear, is the sum of a collection of numbers divided by the number of numbers in the collection.
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Binomial distribution
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.
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Burr distribution
In probability theory, statistics and econometrics, the Burr Type XII distribution or simply the Burr distribution is a continuous probability distribution for a non-negative random variable.
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Cauchy distribution
The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution.
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Chi-squared distribution
No description.
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Confidence interval
In statistics, a confidence interval (CI) is a type of interval estimate, computed from the statistics of the observed data, that might contain the true value of an unknown population parameter.
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CumFreq
In statistics and data analysis the application software CumFreq is a tool for cumulative frequency analysis of a single variable and for probability distribution fitting.
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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.
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Dagum distribution
The Dagum distribution is a continuous probability distribution defined over positive real numbers.
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Density estimation
In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function.
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Expected value
In probability theory, the expected value of a random variable, intuitively, is the long-run average value of repetitions of the experiment it represents.
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Exponential distribution
No description.
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Forecasting
Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends.
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Fréchet distribution
The Fréchet distribution, also known as inverse Weibull distribution, is a special case of the generalized extreme value distribution.
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Frequency (statistics)
In statistics the frequency (or absolute frequency) of an event i is the number n_i of times the event occurred in an experiment or study.
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Gompertz distribution
No description.
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Goodness of fit
The goodness of fit of a statistical model describes how well it fits a set of observations.
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Gumbel distribution
In probability theory and statistics, the Gumbel distribution (Generalized Extreme Value distribution Type-I) is used to model the distribution of the maximum (or the minimum) of a number of samples of various distributions.
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Histogram
A histogram is an accurate representation of the distribution of numerical data.
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Hydrology
Hydrology is the scientific study of the movement, distribution, and quality of water on Earth and other planets, including the water cycle, water resources and environmental watershed sustainability.
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Kurtosis
In probability theory and statistics, kurtosis (from κυρτός, kyrtos or kurtos, meaning "curved, arching") is a measure of the "tailedness" of the probability distribution of a real-valued random variable.
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L-moment
In statistics, L-moments are a sequence of statistics used to summarize the shape of a probability distribution.
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Laplace distribution
In probability theory and statistics, the Laplace distribution is a continuous probability distribution named after Pierre-Simon Laplace.
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Linear map
In mathematics, a linear map (also called a linear mapping, linear transformation or, in some contexts, linear function) is a mapping between two modules (including vector spaces) that preserves (in the sense defined below) the operations of addition and scalar multiplication.
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List of probability distributions
Many probability distributions that are important in theory or applications have been given specific names.
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Log-logistic distribution
No description.
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Log-normal distribution
In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed.
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Logistic distribution
In probability theory and statistics, the logistic distribution is a continuous probability distribution.
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Maximum likelihood estimation
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model, given observations.
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Maximum spacing estimation
In statistics, maximum spacing estimation (MSE or MSP), or maximum product of spacing estimation (MPS), is a method for estimating the parameters of a univariate statistical model.
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Mean
In mathematics, mean has several different definitions depending on the context.
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Method of moments (statistics)
In statistics, the method of moments is a method of estimation of population parameters.
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Mixture distribution
In probability and statistics, a mixture distribution is the probability distribution of a random variable that is derived from a collection of other random variables as follows: first, a random variable is selected by chance from the collection according to given probabilities of selection, and then the value of the selected random variable is realized.
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Mode (statistics)
The mode of a set of data values is the value that appears most often.
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Normal distribution
In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.
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Numerical method
In numerical analysis, a numerical method is a mathematical tool designed to solve numerical problems.
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Observational error
Observational error (or measurement error) is the difference between a measured value of a quantity and its true value.
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Parameter
A parameter (from the Ancient Greek παρά, para: "beside", "subsidiary"; and μέτρον, metron: "measure"), generally, is any characteristic that can help in defining or classifying a particular system (meaning an event, project, object, situation, etc.). That is, a parameter is an element of a system that is useful, or critical, when identifying the system, or when evaluating its performance, status, condition, etc.
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Pareto distribution
No description.
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Prediction
A prediction (Latin præ-, "before," and dicere, "to say"), or forecast, is a statement about a future event.
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Probability
Probability is the measure of the likelihood that an event will occur.
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Probability density function
In probability theory, a probability density function (PDF), or density of a continuous random variable, is a function, whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample.
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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.
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Product distribution
A product distribution is a probability distribution constructed as the distribution of the product of random variables having two other known distributions.
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Q–Q plot
In statistics, a Q–Q (quantile-quantile) plot is a probability plot, which is a graphical method for comparing two probability distributions by plotting their quantiles against each other.
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Return period
A return period, also known as a recurrence interval (sometimes repeat interval) is an estimate of the likelihood of an event, such as an earthquake, flood, landslide, or a river discharge flow to occur.
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Skewness
In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
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Standard deviation
In statistics, the standard deviation (SD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values.
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Student's t-distribution
In probability and statistics, Student's t-distribution (or simply the t-distribution) is any member of a family of continuous probability distributions that arises when estimating the mean of a normally distributed population in situations where the sample size is small and population standard deviation is unknown.
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Survival function
The survival function is a function that gives the probability that a patient, device, or other object of interest will survive beyond any given specified time.
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Uncertainty
Uncertainty has been called "an unintelligible expression without a straightforward description".
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Variance
In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its mean.
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Weibull distribution
No description.
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References
[1] https://en.wikipedia.org/wiki/Probability_distribution_fitting
