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Curvilinear Regression শব্দের বাংলা অর্থ: বক্ররেখা নির্ভরণ
Curvilinear Regression Meaning In Bengali বক্ররেখা নির্ভরণ
Curvilinear Regression
Definition
1) Curvilinear regression is a statistical method used to model relationships between two variables by fitting a curve instead of a straight line to the data points. This allows for capturing non-linear patterns in the data.
2) In curvilinear regression, the relationship between the independent and dependent variables is described using a curved line or function, which provides a better fit to the data compared to linear regression when the relationship is non-linear.
3) Curvilinear regression is commonly used in fields such as biology, psychology, and social sciences to analyze complex relationships between variables that do not follow a straight-line pattern.
Examples
Curvilinear Regression Example in a sentence
1) The curvilinear regression demonstrated a U-shaped relationship between age and cognitive function.
2) Researchers found a strong curvilinear regression between exercise intensity and heart rate.
3) The data analysis revealed a significant curvilinear regression between temperature and plant growth.
4) The study showed a curvilinear regression between sleep duration and reaction time.
5) The curvilinear regression model illustrated the non-linear association between income and happiness.
6) The curvilinear regression indicated an inverted U-shaped pattern between stress levels and productivity.
7) Scientists observed a curvilinear regression between medication dosage and symptom relief.
8) The curvilinear regression analysis suggested a bell-shaped curve in the relationship between food consumption and weight gain.
9) The research findings pointed to a curvilinear regression between study time and exam performance.
10) The statistical analysis identified a curvilinear regression between sunlight exposure and vitamin D levels.
Part of Speech
Curvilinear Regression (Noun)
Synonyms
Encyclopedia
Curvilinear regression is a statistical method used to model relationships between two variables by fitting a curve instead of a straight line to the data points. This allows for capturing non-linear patterns in the data.
In curvilinear regression, the relationship between the independent and dependent variables is described using a curved line or function, which provides a better fit to the data compared to linear regression when the relationship is non-linear.
Curvilinear regression is commonly used in fields such as biology, psychology, and social sciences to analyze complex relationships between variables that do not follow a straight-line pattern.
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