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International Statistical Review / Revue Internationale de Statistique, 1972
I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and ...
J. C. Gower, W. W. Cooley, P. R. Lohnes
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I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and ...
J. C. Gower, W. W. Cooley, P. R. Lohnes
semanticscholar +3 more sources
Technometrics, 1973
Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate
H. Herne +2 more
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Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate
H. Herne +2 more
+4 more sources
Multivariate data analysis of NMR data
Journal of Pharmaceutical and Biomedical Analysis, 1991Multivariate methods based on principal components (PCA and PLS) have been used to reduce NMR spectral information, to predict NMR parameters of complicated structures, and to relate shift data sets to dependent descriptors of biological significance.
U, Edlund, H, Grahn
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Multivariate Data Analysis of Proteome Data
2006We present the background for multivariate data analysis on proteomics data with a hands-on section on how to transfer data between different software packages. The techniques can also be used for other biological and biochemical problems in which structures have to be found in a large amount of data. Digitalization of the 2D gels, analysis using image
Kåre, Engkilde +2 more
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SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics
, 2018This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences.
Daniel J. Denis
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Multivariate Data and Multivariate Analysis
2005Multivariate data arise when researchers record the values of several random variables on a number of subjects or objects or perhaps one of a variety of other things (we will use the general term “units”) in which they are interested, leading to a vector-valued or multidimensional observation for each.
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Experimental Design and Data Analysis for Biologists
, 2002Applying statistical concepts to biological scenarios, this established textbook continues to be the go-to tool for advanced undergraduates and postgraduates studying biostatistics or experimental design in biology-related areas.
G. Quinn, M. Keough
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2016
This short chapter shows how the statistical properties of higher-dimensional data can be visualized: with 3D-surfaces, Scatterplot Matrices, and Correlation Matrices.
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This short chapter shows how the statistical properties of higher-dimensional data can be visualized: with 3D-surfaces, Scatterplot Matrices, and Correlation Matrices.
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Multivariate Analysis of Incomplete Mapped Data
Transactions in GIS, 2003AbstractClassical multivariate analyses are based on matrix algebra and enable the analysis of a table containing measurements of a set of variables for a set of sites. Incomplete mapped data consist of measurements of a set of variables recorded for the same geographical region but for different zonal systems and with only a partial sampling of this ...
Dray, S., Pettorelli, N., Chessel, D.
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