Statistics were used by sedimentologists and paleontologists to describe populations with some univariate, bivariate, and multivariate statistics used by a few avant garde workers.
The three-dimensional multivariate statistics used in the following are constructed from a collection of 746 quasi-equidistant snapshots of the coupled Earth dynamo taken during a free-run (a numerical integration unconstrained by data) spanning approximately 67,000 years.
Liver and blood plasma were profiled across 14 days, and multivariate statistics used to identify perturbed pathways.
In this approach, large data sets of chemical descriptors are used for characterizing chemicals, and multivariate statistics is used to extract those chemical descriptors that have the highest predictive values for odor responses of individual receptors or receptor families.
Briefly, this method is composed of three steps: (i) label the patterns from the test set (an unlabelled data block), using an unsupervised method; (ii) compute some statistics from the train and test sets, conditioned to the given class labels for train set; and (iii) compare the training and testing statistics using a multivariate hypothesis test.
Multivariate statistics were used generally, but given the small numbers with placement concerns and poor thesis performance, these were analysed using univariate tests only.
Because of the large number of reflectance spectra in the image cube, multivariate statistics were used to reduce the dimensionality of the data.
Multivariate statistics were used to extract the main driving forces for changes in vegetation patterns out of a complex landscape ecological data set.
Univariate, bivariate, and multivariate statistics were used to describe the data.
Multivariate statistics was used for a preliminary inspection of the technical quality of the data, as a whole (taking about 1 h of analysis, Figure 1A).
