Examples of using Regression model in English and their translations into Greek
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Do they know anything about regression models?
Then, quasi-Poisson models and Beta regression models are developed for linking road safety management indicators
Traditional regression models(whether they are linear,
Regression models were developed including state
Using regression models, Aycock et al. found that only sexist gender harassment was associated with a deteriorated sense of belonging.
Using linear and non-linear regression models statistical tests were performed
Linear and non-linear regression models were developed and resulted in quantification of the impact of each variable to the number of fatalities in road accidents.
Nearly all real-world regression models involve multiple predictors, and basic descriptions of
Linear regression models were created using the concentrations of TNF-α,
Researchers used regression models to estimate percentage changes in concentration of VOCs in blood to establish whether a dose-response relationship existed.
For example, weighted least squares is a method for estimating linear regression models when the response variables may have different error variances,
Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally.
The combination of swept or unswept matrices provides an alternative method for estimating linear regression models.
Fatality and injury risk can be then modeled through multilevel logistic regression models, which account for the hierarchical dependences of the road accident process.
researchers usually include several variables in their regression models in addition to the variable of primary interest.
This ratio was applied to the residuals from regression models and is commonly known as the Durbin- Watson statistic for testing the null hypothesis that the errors are serially independent against the alternative that they follow a stationary first order autoregression.
the problem of numerical methods for linear least squares is an important one because linear regression models are one of the most important types of model,
Gibbs sampling of a probit model is possible because regression models typically use normal prior distributions over the weights,
The numerical methods for linear least squares are important because linear regression models are among the most important types of model,
the problem of numerical methods for linear least squares is an important one because linear regression models are one of the most important types of model,