Examples of 'linear regressions' in a sentence
Meaning of "linear regressions"
This phrase refers to a statistical modeling technique used to analyze the relationship between two or more variables. Linear regressions involve fitting a straight line that best represents the relationship between the variables, enabling predictions or explanations based on the observed data
How to use "linear regressions" in a sentence
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linear regressions
Linear regressions and mediation analyses were computed.
Let us now consider linear regressions of standard scores.
Linear regressions and confidence intervals.
Spearman rank correlations and linear regressions were performed.
Multiple linear regressions were used for multivariate analysis.
The models are linear regressions.
Linear regressions with one regressor.
The multivariate analysis was performed using multiple linear regressions.
The use of linear regressions is particularly indicated.
Simple or multivariate linear regressions.
Like all linear regressions the logistic regression is a predictive analysis.
The preliminary analysis involves two simple linear regressions.
Logistic and linear regressions were combined with multivariate autoregressive techniques.
Separate analyses were done for each sex using multiple linear regressions.
We used linear regressions and akaike information criterion to assess these relationships.
See also
Follows from the theory of least squares optimization of linear regressions.
It was realized multiple linear regressions to contemplate presidential governments since fernando henrique cardoso.
The visual inspection of the distributions allowed characterizing the linear regressions as homoscedastic.
We searched for linear regressions between maximal handgrip strength and maximal performances.
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.
Multiple linear regressions were used to investigate the relationship between independent and dependent variables.
Learning how to draw graphical representations of experimental data and how to make linear regressions.
Multiple linear regressions were used if more than one predictor showed association with each outcome.
The lower developmental thresholds and thermal summations for each stage were calculated from linear regressions.
Linear regressions show that mRNA levels in donor cells versus microvesicles were not well correlated.
We used the R statistical software to compute correlations and perform linear regressions.
Introduction Simple linear regressions can predict the behavior of one variable by another.
Additionally, we developed statistical models through multiple linear regressions.
How to perform linear regressions with pvalue . io.
Linear regressions of the following type were thus calculated,.
To do this, multiple linear regressions are conventionally used.
Association analyses between variables were performed by comparing groups, correlations, and linear regressions.
In addition, multiple linear regressions were performed.
To do this, predictive models using supervised learning and multiple linear regressions are used.
Why limit yourself to linear regressions in estimating multiples?
To answer this question, I performed linear regressions.
Multilevel linear regressions were used to investigate intra-individual changes across time.
For the same period, slopes of plotwise linear regressions were tested for significance.
Multiple linear regressions were done to identify predictor variables for 25 cognitive tests scores dependent variables.
This model is based on simple linear regressions and is written as follows, n m.
Simple linear regressions are used to identify a correlation between 2 variables and to quantify this relationship.
Most estimates were derived using Ford-Walford plots, which are less reliable than non - linear regressions.
Least squares linear regressions are usually used, although several other methods exist as well.
A statistical package ( SPSS ) was used to estimate linear regressions.
Results, Six multiple linear regressions were conducted to predict six dimensions of psychological distress.
This hypothesis was verified using multiple linear regressions and a sample of 1492 French-canadian pupils.
Linear regressions are performed and IC50 's are calculated using computer software.
The R 2 values from linear regressions of existing model mortality patterns on the INDEPTH components.
Based on the linear regressions in Figure 48, the expected pH and conductivity at 25°C were calculated.
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The risk of spurious regressions was thereby eliminated
Regressions were computed separately for each outcome
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