Sentence examples for multivariate data in from inspiring English sources

Logistic regression is the most common statistical model for processing multivariate data in the medical literature.

The results for normal and non-normal multivariate data in Tables 1 and 2 are similar and can be summarized as follows: For clean sample data, test statistic (E_{k1}) based on classic estimators is close to 1.

In examining the NMR multivariate data in more detail, we found that the post-group can be divided into two subgroups along the Y axis of the plot (See the dotted red lines in Fig. 3), whereas the pre-group is clustered tightly without such intra-group separation.

Interpretable principal components scores were produced summarizing the multivariate data in terms of standardized variables with zero mean and standard deviation of one.

PCA has been introduced by Pearson (1901) and Hotelling (1933) to describe the variation of multivariate data in terms of a set of uncorrelated variables.

A principal component analysis (PCA) was performed to identify the relationships between the various groups of multivariate data in terms of the similarities or differences.

A variety of topics is explored, from the importance of theory for the scientific method in general to multivariate data analysis in particular.

A number of examples illustrate the use of multivariate data analysis in chemistry: The origin of an organic material found in traces on a Neolithic statuette is identified from GC/MS data.

Biplots are used for multivariate data analysis in areas such as sociology [73], genetics [74] and bibliometrics [75].

For this purpose, the possibility to use multivariate data analysis in combination with statistical design was investigated.

Thus, our analysis focused on the development of an easy-using algorithm to extend the application of the Shapiro–Francia test to multivariate data matrix in plant studies.