Bivariate analysis

Waiting time between eruptions and the duration of the eruption for the Old Faithful Geyser in Yellowstone National Park, Wyoming, USA. This scatterplot suggests there are generally two "types" of eruptions: short-wait-short-duration, and long-wait-long-duration.

Bivariate analysis is one of the simplest forms of quantitative (statistical) analysis.^[1] It involves the analysis of two variables (often denoted as X, Y), for the purpose of determining the empirical relationship between them.^[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 linear regression).^[2]

Bivariate analysis can be contrasted with univariate analysis in which only one variable is analysed.^[1] Like univariate analysis, bivariate analysis can be descriptive or inferential. It is the analysis of the relationship between the two variables.^[1] Bivariate analysis is a simple (two variable) special case of multivariate analysis (where multiple relations between multiple variables are examined simultaneously).^[1]

^ ^a ^b ^c ^d ^e Earl R. Babbie, The Practice of Social Research, 12th edition, Wadsworth Publishing, 2009, ISBN 0-495-59841-0, pp. 436–440
^ Bivariate Analysis, Sociology Index

[babbie-1] Earl R. Babbie, The Practice of Social Research, 12th edition, Wadsworth Publishing, 2009, ISBN 0-495-59841-0, pp. 436–440

[2] Bivariate Analysis, Sociology Index

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