Translation of "Multivariate statistik" in English

Univariate and multivariate statistics, including Canonical Correspondence Analysis and Discriminant Analysis will be used.

Here are some examples of problems which may require multivariate statistics:

Therefore, multivariate statistics (principal component analysis) is used to differentiate between such patterns.

The lecture, as well as the seminar "Inferential and Multivariate Statistics" (Schließende und multivariate Statistik) are offered each winter semester.

While physico-chemical descriptors like molecular weight, (partial) charge, solubility, etc. can mostly be computed directly based on the molecule's structure, pharmacological descriptors can be derived only indirectly using involved multivariate statistics or experimental (screening, bioassay) results.

Qualitative methods like focused group discussions or narrative interviews and quantitative methods like multivariate statistics, multiple regression models and survival-time analyses are combined (if needed), and supplemented by new, participatory and experimental methods, e.g. citizen science, mental maps etc.

The seminar "Inferential and Multivariate Statistics" (Schließende und multivariate Statistik) teaches interpretative evaluation of statistic data and methods for multivariate data analysis.

Structural equation modeling tools let you build structural equation models with more accuracy than standard multivariate statistics models using intuitive drag-and-drop functionality.

For more than eight years she developed solutions in the areas of pattern recognition, machine learning and multivariate statistics for companies as well as several research institutes at the RWTH Aachen University.

B. Flury, H. Riedwyl Angewandte multivariate Statistik Stuttgart: Gustav Fischer Verlag, 1983 Contains an excellent introduction to discriminant analysis (in German language, recommended).

Usability interviews, Web and business intelligence (BI) analytics, multivariate statistics, and data mining are the tricks of the trade they use to help our teams understand what our users are doing and why.

We use multivaraite statistics to combine nitrogen source and trophic position proxies with biotic and abiotic variables measured on site in the field to generate a mechanistic understanding how functional biodiversity fosters resilience in plankton in a changing environment.

Many of the methods for data analysis are based on multivariate statistics, which poses an additional problem to the beginner: multivariate statistics cannot be understood without a profound knowledge of simple statistics.

This is quite important for multivariate statistics because many methods of multivariate statistics are based on solving systems of (linear) equations.

Anastasija is a postdoctoral researcher at the Swiss Institute for Empirical Economic Research with a strong interest in financial markets and multivariate analysis.

We use studies at the landscape level, analyses of large databases with multivariate statistics, modelling and geospatial analysis employing geographical information systems (GIS), as well as transdisciplinary workshops, focus groups, interviews and citizen science approaches.

More detailed information on methods of multivariate statistics can be obtained from the relevant literature.

Among the multivariate statistical techniques, the discriminant analysis techniques are particularly preferred.

The analysis was carried out using a multivariate statistic according to the "partial least squares" method.

The covariance plays an important role in multivariate statistics.

These profiles were analyzed by multivariate statistics to find the most significant biomarkers.

Her work covers multivariate statistical analysis as well as the cartographic representation of research results.

He is the author of numerous research papers in multivariate analysis, nonparametric statistics, extreme-value theory, and multiple-criteria decision analysis.

It is moreover possible to vary, in addition to the discriminator generation method, also the multivariate statistical techniques used.

In the fifities he also worked on multivariate analysis, and developed the text "Multivariate Analysis" in 1957.

Often it will not be possible to exploit the full potential of the survey questionnaires because an over-detailed multivariate analysis will very soon show up the statistical problem of using small numbers.

Of course, peak tables or, for example, evaluation using known methods of multi-variance statistics can also be used for special applications.

In the training run, a discrimination algorithm is performed at least once, in which a discriminator set is generated from measurements of S(t), a score is generated in each case from the latter with a multivariate statistical technique and it is checked whether the scores can be divided into separate subsets, in which the concentrations are correctly assigned to the sub-sections of the calibration curve.