Exemplos de uso de Simple linear regression em Inglês e suas traduções para o Português
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To calculate the simple linear regression equation.
A simple linear regression is then fitted to the log-log plot.
In some studies,only simple linear regression was studied.
Simple linear regression analyzes were used to evaluate change in the HRQoL at T2.
Table 4 shows the results of simple linear regression analysis.
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Then, a simple linear regression was developed for each group High MIL and Low MIL.
Such variables presented p< 0.20 in the simple linear regression analysis Table 2.
Simple linear regression analysis was used in order to select the variables under study.
Analysis of the residuals of the simple linear regression indicated that the models were well adjusted.
Simple linear regression analysis showed a correlation of r=0.707 R=0.501; p.
Statistical analysis was performed using the Pearson correlation test and simple linear regression.
In this sense, simple linear regression models were adjusted for each temporal series.
Finally, we carried out bivariate analyses between exposures andHEI means by simple linear regression.
If we have a simple linear regression model, we have some equation like Y=A1X1+A2X2. Plus.
This relation was evaluated at moments before and after nasal vasoconstriction,from the model of simple linear regression.
Simple linear regression model was used to analyze and compare mortality trends.
Table 5 presents the results of simple linear regression, and the outcome were hospitalizations for ACSC.
Simple linear regression evaluated the identification time for each structure per exam.
The first tested model was the simple linear regression 0+?1X, followed by the higher-order models.
Simple linear regression analysis was used to verify possible interrelationships between the measurements.
The estimates using the complex sampling design were made using simple linear regression, trend graphs and Boxplot.
The simple linear regression models were tested at the second and third orders and with exponential functions.
Table 2 Bivariate analysis between weight-for-length, weight-for-age, andcategorical covariables simple linear regression.
A simple linear regression test was performed for the significant variables in the association tests.
Bivariate analyses were carried out using Pearson's chi-square test and simple linear regression followed by logistic regression. .
A simple linear regression(rls) showed that 9 of the 12 variables identified by the director alone impacted the ro of mining.
To identify the scenario, data from the main information systems were used,verifying the temporal tendency through simple linear regression.
Thumbnail Table 3 Simple linear regression analysis of ferritin levels in newborns according to socioeconomic, biological and obstetric variables.
We used the Pearson correlations to analyze the correlations between satisfaction and loyalty, and simple linear regression to verify the predictive effect of satisfaction on loyalty.
Crude analyses used simple linear regression categorical covariables and central exposure variables and Spearman's correlation test numerical covariables.