DataTerminology.comNEW
Also known as: Target Variable
The outcome being predicted or measured, whose values are influenced by one or more independent variables.
DESCRIPTION
A dependent variable is the response of interest in statistical modeling and supervised learning. In regression it is continuous, while in classification it takes discrete classes. Its variation is explained by predictors (independent variables), and correct specification is key to valid inference. In causal analyses, the dependent variable represents the effect of treatments or interventions. Careful labeling and consistent encoding ensure clean training targets.
ALTERNATIVE DEFINITIONS
Wikipedia
In an experiment, the dependent variable is the variable being tested and measured, and is dependent on the independent variable.
Defines experimental context and dependency on independent variables.
Encyclopaedia Britannica
Dependent variable, in an experiment, is the variable being studied and measured; it is expected to change when the independent variable is changed.
Emphasizes expected change under manipulation of the independent variable.
Penn State Eberly College of Science
The dependent variable (response) is the outcome we wish to predict or explain using one or more independent variables.
Uses regression terminology (response/predictors).
scikit-learn
Target: The variable that supervised learning algorithms try to predict; also called the dependent variable.
Connects ML terminology (target) to the statistical term.
RELATED TERMS
Response Variable Predictor Outcome Regression Analysis Classification Supervised Learning Causal Inference Treatment Effect
COMPETING TERMS
KNOWLEDGE AREAS
TARGET AUDIENCE
Data Scientist Data Analyst AI Engineer Information Analyst
EXTERNAL SOURCES
- Wikipedia - Dependent and independent variables
- scikit-learn - ML glossary definition of target
- Penn State - Regression terminology overview
- Khan Academy - Video on identifying variables
TOP QUESTIONS
How is the Dependent Variable used in supervised learning?
It is the target label that algorithms learn to predict from features during training.
Category: Application
What is the difference between Dependent Variable and label?
They are synonymous: the label or target is the dependent variable in ML contexts.
Category: Misunderstanding
How do you encode a categorical Dependent Variable?
Common encodings include label encoding and one-vs-rest targets; choose methods that align with the model.
Category: Requirements
What risks exist when defining the Dependent Variable?
Label leakage, mislabeling, and target imbalance can bias models and invalidate evaluation.
Category: Risk
How is the Dependent Variable used in causal inference?
It represents the outcome affected by treatment, central to estimating causal effects.
Category: Concept
What is a common mistake around the Dependent Variable?
Using post-treatment variables as targets, which can bias causal analyses.
Category: Mistakes
How do you pick a Dependent Variable for a business problem?
Align with measurable outcomes that reflect value, are stable to define, and have reliable labels.
Category: Guidance
How to handle skewed Dependent Variables?
Consider transformations, robust losses, or resampling strategies to stabilize learning.
Category: Management
What metrics evaluate predictions of the Dependent Variable?
Use metrics matched to target type, like RMSE, MAE, accuracy, AUC, or F1.
Category: Testing