Sentence examples for between variables based on from inspiring English sources
This result is evident in that validity related to the fit between measures and the underlying constructs they are designed to represent (construct validity) and the ability to make recommendations regarding the relationship between variables based on statistical evidence about co-variation and prediction (statistical conclusion validity) do not differ by geographic region.
A distance between variables based on prior knowledge is calculated and added to the data based distance.
A Bayesian network is generated depicting the relation between variables based on the joint conditional probability distributions of the variables from the data set.
In the hypothesised model, assumptions are made regarding the strength of associations between variables based on the quantity and quality of evidence.
In an interesting and quite exhaustive review on Random Forests (RF) methodology in bioinformatics Touw et al. address among other topics the problem of the detection of interactions between variables based on RF methodology.
We confirmed assumptions for regression analyses by checking for linearity between variables based on plotting and curve-fitting procedures, by excluding multicollinearity based on variance inflation factors, and by assessing normal distribution of residuals graphically.
Finally, the relationship between several variables based on data from the Matlab software fit has been obtained.
To isolate anthropogenic carbon in the ocean and observe how it has changed through time, Chu used a modeling technique known as extended multiple linear regression — a statistical method that models the relationships between given variables, based on observed data.
To test for independence between two variables based on observed response frequencies, we use chi-square tests.
The extraction of information on interactions between predictor variables based on random forests is not trivial.
Polychoric correlations estimate the correlation between categorical variables based on the assumption that the observed categorical values are functions of latent normal random variables.
