Univariate Numerical Dataset

Context:
- It can range from being an Unordered Univariate Numerical Dataset to being an Ordered Univariate Numerical Dataset (such as a univariate timeseries).
Example(s):
- {0, 1, 1, 2, 3, NULL, 8, 13, 21}, a portion of a Fibonacci series with missing values.
- …
Counter-Example(s):
See: Univariate Data Analysis, Univariate Numerical Outlier Detection.

References

(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.

http://web.csulb.edu/~msaintg/ppa696/696uni.htm
- QUOTE: Univariate analysis explores each variable in a data set, separately. It looks at the range of values, as well as the central tendency of the values. It describes the pattern of response to the variable. It describes each variable on its own.
  Descriptive statistics describe and summarize data. Univariate descriptive statistics describe individual variables.