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From univariate‐ to multivariate analysis
Statistica Neerlandica, 1972SummaryThis paper is intended for those who are interested in the didactics of multivariate analysis. The problem studied is: how can the transition from univariate ‐ to multivariate analysis be made as simple as possible? Here we provide a simple “codingkey”, which works logically and is easy to remember and to handle.
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2018
We divide microbiome community composition study into two major components: (1) hypothesis testing of taxonomic diversities, OTUs and taxa and (2) analysis of dissimilarities among groups.
Yinglin Xia, Jun Sun, Ding-Geng Chen
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We divide microbiome community composition study into two major components: (1) hypothesis testing of taxonomic diversities, OTUs and taxa and (2) analysis of dissimilarities among groups.
Yinglin Xia, Jun Sun, Ding-Geng Chen
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Simplifying algebraic attacks with univariate analysis
2011 Information Theory and Applications Workshop, 2011The purpose of this paper is to present a more fine-grained view on cryptanalysis of stream ciphers based on LFSRs in terms of the univariate representation and to provide some connections to cyclic codes. A usual way of presenting such ciphers is in terms of multivariate equations over GF(2).
Tor Helleseth, Sondre Rønjom
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Univariate Statistical Analysis
2017This chapter presents basic statistical methods used in describing and analysing univariate data in R. It covers the topics of descriptive and inferential statistics of univariate data, which are mostly treated in introductory courses in Statistics.
Wolfgang Karl Härdle +2 more
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2013
Let us return to our students from the previous chapter. After completing their survey of bread spreads, they have now coded the data from the 850 respondents and entered them into a computer. In the first step of data assessment, they investigate each variable – for example, average respondent age – separately. This is called univariate analysis.
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Let us return to our students from the previous chapter. After completing their survey of bread spreads, they have now coded the data from the 850 respondents and entered them into a computer. In the first step of data assessment, they investigate each variable – for example, average respondent age – separately. This is called univariate analysis.
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Univariate Screening Measures for Cluster Analysis
Multivariate Behavioral Research, 1995lnciusion of irrelevant variables in a cluster analysis adversely affects subgroup recovery. This article examines using moment-based statistics to screen variables; only variables which pass the screening are then used in clustering. Normal mixtures are analytically shown often to possess negative kurtosis.
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Univariate statistical analysis with fuzzy data
Computational Statistics & Data Analysis, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Univariate Singular Spectrum Analysis
2018A concise description of univariate Singular Spectrum Analysis (SSA) is presented in this chapter. A step-by-step guide for performing filtering, forecasting as well as forecasting interval using univariate SSA and associated R codes is also provided. After reading this chapter, the reader will be able to select two basic, but very important, choices ...
Hossein Hassani, Rahim Mahmoudvand
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