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Univariate is a term commonly used in statistics to describe a type of data which consists of observations on only a single characteristic or attribute. A simple example of univariate data would be the salaries of workers in industry. [1]
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional normal distribution to higher dimensions.
In mathematics, a univariate object is an expression, equation, function or polynomial involving only one variable.Objects involving more than one variable are multivariate.
Continuous uniform distribution. One of the simplest examples of a discrete univariate distribution is the discrete uniform distribution, where all elements of a finite set are equally likely.
Simple linear regression is a statistical method used to model the linear relationship between an independent variable and a dependent variable.
In probability theory, a probability density function (PDF), density function, or density of an absolutely 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 ...
In statistics, a unit root test tests whether a time series variable is non-stationary and possesses a unit root.The null hypothesis is generally defined as the presence of a unit root and the alternative hypothesis is either stationarity, trend stationarity or explosive root depending on the test used.
Extreme value theory is used to model the risk of extreme, rare events, such as the 1755 Lisbon earthquake.. Extreme value theory or extreme value analysis (EVA) is the study of extremes in statistical distributions.