Univariate Dataset

A Univariate Dataset is a dataset that contains only one dataset variable.

• Context:
  • It can range from being a Numerical Univariate Dataset to being a Categorical Univariate Dataset.
  • It can be an input to a Univariate Data Analysis Task, such as a point estimation task.
  • It can range from being a Real Univariate Dataset to being a Synthetic Univariate Dataset.
• Example(s):
  • [math]\displaystyle{ \{1, 2.4, 0, -1, \infty\} }[/math]
  • a Univariate Timeseries.
  • …
• Counter-Example(s):
  • a Multivariate Dataset, such as a bivariate dataset.
  • a Categorical Dataset, such as {a, lask, 283}.
• See: Forecasting Task, Univariate Expression, Univariate Function, Univariate Data, Bivariate, Trivariate, Quadrivariate, Multivariate, Univariate Timeseries.

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References

2016

• (Wikipedia, 2016) ⇒ https://en.wikipedia.org/wiki/univariate Retrieved:2016-5-9.
  • … The term is commonly used in statistics to distinguish a distribution of one variable from a distribution of several variables, although it can be applied in other ways as well. For example, univariate data are composed of a single scalar component. In time series analysis, the term is applied with a whole time series as the object referred to: thus a univariate time series refers to the set of values over time of a single quantity. Correspondingly, a "multivariate time series" refers to the changing values over time of several quantities. Thus there is a minor conflict of terminology since the values within a univariate time series may be treated using certain types of multivariate statistical analyses and may be represented using multivariate distributions.

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