Examples of using Multivariate data in English and their translations into Portuguese
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There are several techniques that aid in the interpretation and analysis of multivariate data.
Multivariate data can be converted to spatial signs by scaling each point by its Euclidean norm.
An excellent way for visualising structures within multivariate data is offered by principal component analysis PCA.
Multivariate data analysis applied factor analysis, cluster analysis(hierarchical and k-means) and manova.
Spin models have been used for clustering of multivariate data wherein similarities are translated into coupling strengths.
Analytical techniques, such as mass spectrometry andnuclear magnetic resonance, and multivariate data analysis techniques.
The empirical tests were used in technical analysis multivariate data multiple regression was applied to a sample of 1508 observations comprising 187 banking institutions.
They combine the power of classification methods with the ability of this type of modeling play compactly, multivariate data.
Other graph partition methods==Spin models have been used for clustering of multivariate data wherein similarities are translated into coupling strengths.
The perceptual maps obtained using multidimensional scaling represent a powerful statistical tool for multivariate data analysis.
The sample was non-probabilistic composed of 454 respondents and adopted the multivariate data analysis by structural equation modeling(sem) using smartpls software.
Analysis and visualization of symmetric second order tensor fields are challenging since they generally represent multivariate data.
Sex, age, household income anddemand-control remained independently associated with AH after the multivariate data adjustment, while skin color and professional category have lost their effect.
Motion Chart- Amotion chartis a dynamic bubble chart which allows efficient and interactive exploration andvisualization of longitudinal multivariate Data.
A radar chart is a graphical method of displaying multivariate data in the form of a two-dimensional chart of three or more quantitative variables represented on axes starting from the same point.
The percentage of variance explained by the two scales also demonstrated a good adjustment in multivariate data analysis 64.82 and 55.77.
The multivariate data analysis, specifically the cluster analysis and principal components analysis was used to describe the profile of water quality of the city neighborhoods.
When performing non-selective measurements,a sum signal from several analytes is measured which means that multivariate data analyses such as neural networks have to be used for quantification.
The MCA is a technique of exploratory analysis of multivariate data that enables the visualization of the most important relationships of a large set of variables without a defined structure a priori.
In order to efficiently manage new developments, these experts are daily using various scientific methodologies,including modeling, multivariate data analysis and design of experiments DOE.
The ica is originally a technique applied in multivariate data analysis, which means that it requires measurements from multiple sensors allocated in different positions of the system.
Arecaceae genotypes from different geographical locations were characterized using untargeted metabolomics by liquid chromatography-mass spectrometry(lc-ms)followed by multivariate data analyses.
Probability Theory 2(requires a course in basic calculus orequivalent knowledge), Multivariate Data Analysis(requires courses in basic calculus and linear algebra or equivalent knowledge), Linear Algebra and Algebra.
For the study, data were collected from sites of instituto de pesquisa econômica e aplicada(ipea), da secretaria do tesouro nacional(stn) e do instituto de pesquisa eestratégia econômica do ceará(ipece), on which was applied a multivariate data technique analysis, called factor analysis.
Abstract Principal component analysis(PCA) is used to extract important information from multivariate data which is expressed as a set of new variables called principal components PCs.
This study analyzes the 15 largest companies in the construction of brazil and its results in the years 2009, 2010 and 2011, to observe the relationship between exposure to the environment agency conflict, through industry standards and qualitative indicators that express this conflict, and reflections on their risk indicators anddebt, through the application of multivariate data analysis.
To ascertain the main characteristics that led oil companies to submit comment letters on the DPEA, multivariate data analysis was conducted on the results described above.
This Masters provided me with vast knowledge in areas such as multivariate data analysis, survival analysis and in using Programe R, a very useful tool for the application of statistics mainly in the area of health, which I am linked to professionally.
An example is the symbolic regression,a modeling tool that seeks mathematical expressions of functions to fit a given multivariate data set, mapping input variables to output variables of control.
It was shown that the method works well andis highly accurate in generating multivariate data with marginal poisson distribution structures for different correlations(negative and positive values) and for high and low?. proved the practical benefits of the simulat.