Examples of using Multiple regression in English and their translations into Portuguese
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Computer
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Five variables remained associated with frailty in the multiple regression model Table 3.
Pearson's correlation coefficient was calculated and a multiple regression model was used.
The regionalization model was established using the multiple regression technique.
Multiple regression was used by stepwise method to relate the mean consumption with the thermal environment factors.
The use of multiple regression showed a significant positive relationship between satisfaction with the profession
we could see exactly how the regression coefficients are estimated in a multiple regression.
To select among the potential predictors in multiple regression, we used the backward algorithm.
to code a categorical predictor in a multiple regression.
Statistical analysis of the main components, multiple regression and cluster analysis were used as statistical techniques.
And what you will see is that analysis of variance is just a special case of multiple regression.
model three is the multiple regression with both predictors in there.
factor analysis and multiple regression.
Multiple regression was then conducted in order to establish predictors of stress and coping by associating a dependent variable to independent ones.
So, in a lot of the examples that we did with multiple regression, the predictor variables were continuous
There was a relation found by multiple regression between female home ranges
For multiple regression, which we will do in the next lecture, it's a little more difficult
In the multiple regression analysis among the group with less schooling, maternal age was selected as an explanatory variable
All women were included in the first Poisson multiple regression model, while in the second only multiparous women were.
A multiple regression model was used to identify independent predictors of epicardial fat thickness.
Multiple regression confirmed an association between prevalence of illness