curvilinear regression (Meaning)
curvilinear regression (n)
the relation between variables when the regression equation is nonlinear (quadratic or higher order)
Synonyms & Antonyms of curvilinear regression
No Synonyms and anytonyms found
curvilinear regression Sentence Examples
- Curvilinear regression is a statistical method used to model relationships between variables that are not linear but follow a curve.
- Researchers applied curvilinear regression to analyze the relationship between age and memory decline, finding that memory loss increased with age at a non-linear rate.
- The psychologist used curvilinear regression to examine the association between stress levels and mental health outcomes, revealing a U-shaped relationship.
- Curvilinear regression allows for the identification of optimal conditions within a range of variables, such as the ideal temperature for plant growth.
- The economist employed curvilinear regression to study the impact of inflation rates on economic growth, uncovering a quadratic relationship.
- Curvilinear regression techniques are commonly used in fields such as psychology, economics, and environmental science to model complex relationships.
- The biologist utilized curvilinear regression to analyze the relationship between pesticide exposure and bee population decline, revealing a non-linear pattern.
- Curvilinear regression can provide valuable insights into phenomena where linear models fail to adequately capture the underlying relationships.
- The statistician employed curvilinear regression to examine the relationship between income inequality and social unrest, discovering a curvilinear pattern.
- Curvilinear regression techniques, such as polynomial regression, allow for the exploration of more flexible and nuanced relationships between variables.
FAQs About the word curvilinear regression
the relation between variables when the regression equation is nonlinear (quadratic or higher order)
No synonyms found.
No antonyms found.
Curvilinear regression is a statistical method used to model relationships between variables that are not linear but follow a curve.
Researchers applied curvilinear regression to analyze the relationship between age and memory decline, finding that memory loss increased with age at a non-linear rate.
The psychologist used curvilinear regression to examine the association between stress levels and mental health outcomes, revealing a U-shaped relationship.
Curvilinear regression allows for the identification of optimal conditions within a range of variables, such as the ideal temperature for plant growth.
