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"multiple regression model" is a correct and usable phrase in written English.
It is typically used when discussing statistical analysis or predicting outcomes based on multiple variables. Example: The researchers used a multiple regression model to analyze the relationship between income, education level, and job satisfaction.
Exact(60)
The general form of the multiple regression model is y = β0 + β1x1 + β2x2 +... + βpxp + ε.
A multiple regression model was used for RT predictions.
A multiple regression model is used as statistical tool.
Therefore, another multiple regression model must be calculated by removing the insignificant variable, BS.
To be able to study these potential predictors simultaneously a multiple regression model was adopted.
Variables showing statistical significance in the multiple regression model were kept in the final predictive model.
Since many features can affect the class, therefore multiple regression model is more appropriate.
Figure 1 shows the normal probability plot for the multiple regression model.
A multiple regression model was calculated including all predictors found significant in the simple models.
The multiple regression model for predicting ECB is significant with F (18, 83) = 10.216, p = 0.000.
Results were adjusted for age, gender and education in a multiple regression model.
More suggestions(18)
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multiple well model
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multiple imputation model
multiple mediation model
multiple regression multicollinearity
multiple regression technique
multiple representation model
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multiple change model
multiple mediator model
multiple regression interpolation
multiple temperature model
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