Examples of 'multiple linear' in a sentence
Meaning of "multiple linear"
Multiple linear refers to a statistical modeling technique used to analyze the relationship between multiple independent variables and a single dependent variable. It involves the use of linear equations and coefficients to determine the impact of each independent variable on the outcome
How to use "multiple linear" in a sentence
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multiple linear
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 regressions were used for multivariate analysis.
Coefficients of multiple linear regression model.
Multiple linear regression to forecast the crop yield.
The intervening variables were controlled by multiple linear regression.
Multiple linear wounds of varying depths around the ligatures.
A similar notation is used for multiple linear regression.
Multiple linear regression was used to evaluate the relationship of interest.
An applicable known method is the multiple linear regression.
Multiple linear regression analysis and multilevel analysis were performed.
The tool is controlled along multiple linear or rotational axes.
See also
Multiple linear regression analysis.
A multivariable analysis was also developed using a multiple linear regression.
Multiple linear regression model.
The multivariate analysis was performed using multiple linear regressions.
Multiple linear regression is used to explain the relationship between.
We discuss shortly the global test in multiple linear regression.
Multiple linear regression model and least squares estimation.
Here is a sample on how to use a multiple linear regression to fit a plane.
Multiple linear regression analysis was used to examine possible predictors.
The statistical analysis is performed using multiple linear regression by ols.
Multiple linear regression analysis was used to compare continuous variables.
Residue analysis showed good adjustment of multiple linear regression model.
Multiple linear regression was used to investigate the relationship between variables.
A basic tool for econometrics is the multiple linear regression model.
It was applied multiple linear regression and pearson correlation to identify associations.
The results were also submitted to the multiple linear regression method.
Then the multiple linear regression model was developed in two stages.
Separate analyses were done for each sex using multiple linear regressions.
Multiple linear regression analysis backward method to identify predictors of HRQoL.
Residual analysis of the final model of multiple linear regression was also undertaken.
Multiple linear regression modeling is a standard tool in demography and econometrics.
Data were analyzed using multiple linear regression method with the ols.
The multiple linear regression models initially included all variables with p.
While for the analysis of quality of life we used multiple linear regression.
One multiple linear regression was conducted for each personality trait.
The adjustment for age and gender was performed by multiple linear regression.
The multiple linear regression models are an extension of the simple linear regression.
These eight independent variables were included in the multiple linear regression model.
Multiple linear scans across the first layer of rebars over a rectangular area.
Data were analysed using univariate statistics and multiple linear regression model.
The multiple linear regression model was developed with the stepwise forward procedure.
The evaluation of the proposed correlation is given by applying a multiple linear regression model.
It was realized multiple linear regressions to contemplate presidential governments since fernando henrique cardoso.
Independent correlates of baseline and hyperemic vascular parameters were assessed by multiple linear regressions.
Descriptive statistics and multiple linear regressions were performed for each cluster.
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