Examples of 'multiple linear regression' in a sentence
Meaning of "multiple linear regression"
multiple linear regression: In statistics, multiple linear regression is a mathematical model used to predict the relationship between two or more independent variables and a dependent variable. It is often used in data analysis to study the impact of multiple factors on an outcome, by estimating the linear combination of these factors
How to use "multiple linear regression" in a sentence
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multiple linear regression
To do this we used multiple linear regression models.
Multiple linear regression methods are explored.
This technique is known as multiple linear regression.
Multiple linear regression was used for statistical analysis.
Descriptive summaries as well as multiple linear regression were conducted.
Multiple linear regression to forecast the crop yield.
Coefficients of multiple linear regression model.
The intervening variables were controlled by multiple linear regression.
Multiple linear regression was used to evaluate the relationship of interest.
A similar notation is used for multiple linear regression.
Multiple linear regression analysis and multilevel analysis were performed.
An applicable known method is the multiple linear regression.
Multiple linear regression analysis.
A multivariable analysis was also developed using a multiple linear regression.
Multiple linear regression model.
See also
We discuss shortly the global test in multiple linear regression.
Multiple linear regression is used to explain the relationship between.
Here is a sample on how to use a multiple linear regression to fit a plane.
Multiple linear regression model and least squares estimation.
The statistical analysis is performed using multiple linear regression by ols.
Multiple linear regression analysis was used to examine possible predictors.
Residue analysis showed good adjustment of multiple linear regression model.
Multiple linear regression analysis was used to compare continuous variables.
A basic tool for econometrics is the multiple linear regression model.
Multiple linear regression was used to investigate the relationship between variables.
The results were also submitted to the multiple linear regression method.
It was applied multiple linear regression and pearson correlation to identify associations.
While for the analysis of quality of life we used multiple linear regression.
Then the multiple linear regression model was developed in two stages.
Residual analysis of the final model of multiple linear regression was also undertaken.
Multiple linear regression analysis backward method to identify predictors of HRQoL.
Data were analyzed using multiple linear regression method with the ols.
Multiple linear regression modeling is a standard tool in demography and econometrics.
The adjustment for age and gender was performed by multiple linear regression.
One multiple linear regression was conducted for each personality trait.
These eight independent variables were included in the multiple linear regression model.
The multiple linear regression models initially included all variables with p.
Data were analysed using univariate statistics and multiple linear regression model.
The multiple linear regression models are an extension of the simple linear regression.
The evaluation of the proposed correlation is given by applying a multiple linear regression model.
The multiple linear regression model was developed with the stepwise forward procedure.
They can be found by using solutions of known concentration and multiple linear regression.
We then used multiple linear regression models to determine associations between these variables.
Associations between hsCRP and individual components of MetS were determined by multiple linear regression analysis.
Several multiple linear regression production functions have been developed over a period of time.
The stepwise method was used to include the variables in the multiple linear regression equations.
Multiple linear regression analysis was performed to identify key risk indicators of work disability.
The second equalization function is an affine function which makes use of multiple linear regression.
Multiple linear regression was used to detect the influence of variables over overweight and obesity.
Hearing recovery following grafting in each group was performed using multiple linear regression analysis.
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