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In statistics, bivariate data is data on each of two variables, where each value of one of the variables is paired with a value of the other variable. [1] It is a specific but very common case of multivariate data. The association can be studied via a tabular or graphical display, or via sample statistics which might be used for inference.
[1] Bivariate analysis can be helpful in testing simple hypotheses of association . Bivariate analysis can help determine to what extent it becomes easier to know and predict a value for one variable (possibly a dependent variable ) if we know the value of the other variable (possibly the independent variable ) (see also correlation and simple ...
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 this case, there are two values for which f is maximal: (n + 1) p and (n + 1) p − 1. M is the most probable outcome (that is, the most likely, although this can still be unlikely overall) of the Bernoulli trials and is called the mode. Equivalently, M − p < np ≤ M + 1 − p. Taking the floor function, we obtain M = floor(np). [note 1]