univariate and multivariate statistical analyses (MathWorks Inc)

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MathWorks Inc univariate and multivariate statistical analyses
Univariate And Multivariate Statistical Analyses, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/multivariate+statistical+analyses/pm30503293-2-4-8
Average 90 stars, based on 1 article reviews

univariate and multivariate statistical analyses - by Bioz Stars, 2026-09

90/100 stars

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Article Title: Enteropathogenic Escherichia coli Infection Induces Diarrhea, Intestinal Damage, Metabolic Alterations, and Increased Intestinal Permeability in a Murine Model
Article Snippet: .. For metabolomics data analysis multivariate statistical modelling was performed including principal component analysis (PCA) using the Imperial Metabolic Profiling and Chemometrics Toolbox ( https://github.com/csmsoftware/IMPaCTS ) in MATLAB (Version 2018a, Mathworks Inc) and unsupervised hierarchical clustering analysis (HCA) to unveil metabolic differences between EPEC infected and control mice. ..

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Article Title: Effect of partial root-zone drying irrigation (PRDI) on the biomass, water productivity and carbon, nitrogen and phosphorus allocations in different organs of alfalfa
Article Snippet: Partial root-zone drying irrigation (PRDI) can influence carbon (C), nitrogen (N), and P (phosphorus) allocations in annual crop plants.. This study consisted of a two-factorial split-plot field experiment conducted on Huanghua farmland in western China, and it was focused on investigating the effects of PRDI on the biomass; water productivity; and C, N and P allocations in a perennial plant (alfalfa) from 2016-2017.. The two factors were the irrigation mode (PRDI and conventional furrow irrigation (CFI)) and irrigation volume (70 %-I1, 85 %-I2, 100 %-I3 and 115 %-I4 of the alfalfa water requirement), in which the irrigation mode was the primary plot and the irrigation volume was the subplot.

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Article Title: Factors Predicting Ventriculostomy Revision at a Large Academic Medical Center.
Article Snippet: -METHODS: Using an administrative database and chart review, we identified 101 first-time external ventricular drain placements performed at the bedside.. We collected data regarding demographics, medical comorbidities, complications, and catheter tip location.. We performed univariate and multivariate statistical analyses using MATLAB.

Article Title: Frequency domain projection algorithm
Article Snippet: The PCA may be carried out, for example, by using MATLAB (MathWorks, Inc, Natick Mass., USA) software within Statistical Toolbox/Multivariate Data Analysis/Principal Component Analysis (PCA) and Canonical Correlation.

Article Title: Auditory localization should be considered as a sign of minimally conscious state based on multimodal findings
Article Snippet: Statistical analyses were performed using non-parametric multivariate permutation test ( ) (5000 permutations) with MATLAB 2018a, to test group differences in terms of connectivity and graph theory measures.

Article Title: Krüppel-like factor 6 (KLF6) requires its amino terminal domain to promote villous trophoblast cell fusion.
Article Snippet: Multivariate statistical analyses were implemented in MatLab software.

Article Title: Extraction of Temperature Dependent Parameters for a Commercial Thermoelectric Cooler
Article Snippet: By using MATLAB multivariate regression analysis, the statistical results are shown in Table 3, From the analysis results of 691 sets of data in Table 3, it can be seen, when the degree of freedom is 6 and the significance is 0.05, the R2 is > 95%, so it can be considered that the optimization degree of fitting of the multivariate linear equation is very good and reasonable.

Article Title: Hybrid Cellular Automata Modelling Reveals the Effects of Glucose Gradients on Tumour Spheroid Growth
Article Snippet: A Multivariate Linear Regression Analysis (MLRA) was performed using the builtin MATLAB function mvregress on whole set of samples to obtain the linear regression coefficients for each parameter.

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