multiple regression
Học thuậtThân thiện
A researcher uses multiple regression to analyze the relationship between study hours, sleep, and exam scores.
Definition
- Noun:
- A statistical technique that predicts values of one variable on the basis of two or more other variables: "Multiple regression" is a method used in statistics to understand the relationship between one dependent variable and several independent variables. It allows for the prediction of the dependent variable's value based on the known values of multiple predictors.
Usage Examples
- Noun:
- The researcher used multiple regression to analyze how age, income, and education level influence spending habits.
- Multiple regression showed that both temperature and humidity were significant predictors of energy consumption.
Advanced Usage
- "To run a multiple regression": to perform or execute a multiple regression analysis.
- We need to run a multiple regression to test our hypothesis about these three factors.
- "Multiple regression analysis": the process and results of applying the multiple regression technique.
- The multiple regression analysis provided a model with a high predictive power.
Variants and Related Words
- Regression (noun): A broader statistical method for modeling the relationship between variables. Multiple regression is a specific type of regression.
- Linear regression (noun): A regression analysis that models the relationship between two variables with a straight line. Multiple regression often refers to multiple linear regression.
- Predictor variable (noun): An independent variable used in a regression model to predict the outcome.
- Dependent variable (noun): The outcome variable that the regression model aims to predict or explain.
Synonyms
- Multivariate regression: A synonym often used interchangeably with multiple regression, emphasizing the use of multiple independent variables.
Related Phrases
- Multiple regression model: The specific equation that results from the analysis, describing the relationship between the variables.
- The final multiple regression model included four key predictors.
- Coefficient of multiple determination (R-squared): A statistic from multiple regression that indicates the proportion of variance in the dependent variable explained by the independent variables.
- The R-squared value from the multiple regression was 0.85, indicating a strong model.
A researcher uses multiple regression to analyze the relationship between study hours, sleep, and exam scores.
Noun
- a statistical technique that predicts values of one variable on the basis of two or more other variables