Dependent Random Variable

AKA: Measured Outcome Variable, Explained Experimental Variate.
Context:
- It can be instantiated as a Target Attribute.
- It can range from being a Categorical Target Variable to being an Ordinal Target Variable to being or a Continuous Target Variable.
- It can be specified in a Statistical Model that is based on a Statistical Experiment.
- It can be represented by a Learning Dataset Target Attribute.
- It can (typically) be an Unobserved Variable during a Prediction Phase.
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Example(s):
- a ...
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Counter-Example(s):
- Independent Random Variable.
- a Latent Variable, such as a Confounding Random Variable.
- a Random Variate.
See: Variable, Response Rate.

References

http://en.wikipedia.org/wiki/Dependent_and_independent_variables#Dependent_variable
- A dependent variable is also known as a "response variable", "regressand", "measured variable", "responding variable", "explained variable", "outcome variable", "experimental variable", and "output variable".^[1]
  If the independent variable is referred to as an "explanatory variable" (see above) then the term "response variable" is preferred by some authors for the dependent variable.

↑ Hastings, Nancy Baxter. Workshop calculus: guided exploration with review. Vol. 2. Springer Science & Business Media, 1998. p. 31

http://en.wikipedia.org/wiki/Dependent_and_independent_variables
- … In statistics, the dependent/independent variable terminology is used more widely than just in relation to controlled experiments. For example the data analysis of two jointly varying quantities may involve treating each in turn as the dependent variable and the other as the independent variable. However, for general usage, the pair response variable and explanatory variable is preferable as quantities treated as "independent variables" are rarely statistically independent.^[1]^[2]
  Depending on the context, an independent variable is also known as a "predictor variable," "regressor," "controlled variable," "manipulated variable," "explanatory variable," "exposure variable," and/or "input variable."^[3] A dependent variable is also known as a "response variable," "regressand," "measured variable," "observed variable," "responding variable," "explained variable," "outcome variable," "experimental variable," and/or "output variable."^[4]

↑ Everitt, B.S. (2002). Cambridge Dictionary of Statistics, CUP. ISBN 0-521-81099-x
↑ Dodge, Y. (2003). The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9
↑ Dodge, Y. (2003). The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9 (entries for "independent variable" and "regression")
↑ Dodge, Y. (2003). The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9 (entry for "regression")

http://en.wiktionary.org/wiki/dependent_variable
- dependent variable (plural dependent variables)
  - 1. (algebra) In an equation, the variable whose value depends on one or more variables in the equation. In the equation z = x2 + y, z is the dependent variable.
  - 2. In sciences, an outcome measured to see the effectiveness of the treatment.

http://www.ncsu.edu/labwrite/po/dependentvar.htm
- A dependent variable is what you measure in the experiment and what is affected during the experiment. The dependent variable responds to the independent variable. It is called dependent because it "depends" on the independent variable. In a scientific experiment, you cannot have a dependent variable without an independent variable.
  Example: You are interested in how stress affects heart rate in humans. Your independent variable would be the stress and the dependent variable would be the heart rate. You can directly manipulate stress levels in your human subjects and measure how those stress levels change heart rate.

(Johnson & Wichern, 1998) ⇒ Richard A. Johnson, and Dean W. Wichern. (1998). “Applied Multivariate Statistical Analysis, 4th ed." Prentice hall, 1992. ISBN:013834194X
- QUOTE: Regression analysis is the statistical methodology for predicting values of one or more response (dependent) variables from a collection of predictor (independent) variable values. It can also be used for assessing the effects of the predictor variables on the responses. Unfortunately, the name regression culled from the title of the first paper on the subject by F. Galton [13], in no way reflects either the importance or breath of application of this methodology. … Let [math]\displaystyle{ z_1, z_2, ..., z_r }[/math] be [math]\displaystyle{ r }[/math] predictor variables through to be related to a [[response variable [math]\displaystyle{ Y }[/math] …