Results 301 to 310 of about 25,895,715 (350)
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Chaos: An Interdisciplinary Journal of Nonlinear Science
The acceleration in the field of data science is well known [see, e.g., D. Donoho, J. Comput. Graph. Stat. 26(4), 745–766 (2017) and references therein]. Improvements in technology for acquisition, storage, and processing have made unheard of amounts of data available to scientists; in parallel with that, the pace of methodological advance has also ...
Elizabeth Bradley +2 more
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The acceleration in the field of data science is well known [see, e.g., D. Donoho, J. Comput. Graph. Stat. 26(4), 745–766 (2017) and references therein]. Improvements in technology for acquisition, storage, and processing have made unheard of amounts of data available to scientists; in parallel with that, the pace of methodological advance has also ...
Elizabeth Bradley +2 more
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2010
Gene expression profiling has revolutionized functional genomics research by providing a quick handle on all the transcriptional changes that occur in the cell in response to internal or external perturbations or developmental programs. Microarrays have become the most popular technology for recording gene expression profiles.
Saroj K, Mohapatra, Arjun, Krishnan
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Gene expression profiling has revolutionized functional genomics research by providing a quick handle on all the transcriptional changes that occur in the cell in response to internal or external perturbations or developmental programs. Microarrays have become the most popular technology for recording gene expression profiles.
Saroj K, Mohapatra, Arjun, Krishnan
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WIREs Cognitive Science, 2010
AbstractBayesian methods have garnered huge interest in cognitive science as an approach to models of cognition and perception. On the other hand, Bayesian methods for data analysis have not yet made much headway in cognitive science against the institutionalized inertia of 20th century null hypothesis significance testing (NHST).
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AbstractBayesian methods have garnered huge interest in cognitive science as an approach to models of cognition and perception. On the other hand, Bayesian methods for data analysis have not yet made much headway in cognitive science against the institutionalized inertia of 20th century null hypothesis significance testing (NHST).
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Annual Review of Psychology, 1998
▪ Abstract This chapter reviews recent developments in the analysis of categorical and contingency-table data. The first portion examines developments in model testing and selection. The second portion examines work on models for the structure of dependence.
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▪ Abstract This chapter reviews recent developments in the analysis of categorical and contingency-table data. The first portion examines developments in model testing and selection. The second portion examines work on models for the structure of dependence.
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European Journal of Drug Metabolism and Pharmacokinetics, 1993
In recent years there has been a growing interest in techniques capable of analyzing sparse data, particularly gathered during Phase III clinical trials, and there is now pressure on manufacturers to obtain more kinetic and dynamic information from Phase III studies.
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In recent years there has been a growing interest in techniques capable of analyzing sparse data, particularly gathered during Phase III clinical trials, and there is now pressure on manufacturers to obtain more kinetic and dynamic information from Phase III studies.
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Air Medical Journal, 2009
This 13th article of the Basics of Research series is first in a short series on statistical analysis. These articles will discuss creating your statistical analysis plan, levels of measurement, descriptive statistics, probability theory, inferential statistics, and general considerations for interpretation of the results of a statistical analysis.
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This 13th article of the Basics of Research series is first in a short series on statistical analysis. These articles will discuss creating your statistical analysis plan, levels of measurement, descriptive statistics, probability theory, inferential statistics, and general considerations for interpretation of the results of a statistical analysis.
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Independent component analysis for noisy data — MEG data analysis
Neural Networks, 2000Independent component analysis (ICA) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such as electroencephalography (EEG), magnetic resonance imaging (MRI), and magnetoencephalography (MEG). However, many problems remain. In most cases, neurobiological data contain
S, Ikeda, K, Toyama
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Research on Big Data Analysis Data Acquisition and Data Analysis
2021 International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA), 2021Using big data analysis algorithm, this paper discusses the source of data acquisition, points out the technical characteristics of data source, and explains the data acquisition methods and requirements. Clear the purpose of big data analysis, build data analysis system, describe the process of data analysis. There are four steps in big data analysis:
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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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Movement Disorders Clinical Practice
What are statistics Good for in human research studies? Studies conducted on human beings may have different objectives and designs, but they all share some common principles. 1 We outline these principles as a cycle, shown in Figure 1. The first step is to obtain a sample from a population.
Santiago Perez‐Lloret +2 more
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What are statistics Good for in human research studies? Studies conducted on human beings may have different objectives and designs, but they all share some common principles. 1 We outline these principles as a cycle, shown in Figure 1. The first step is to obtain a sample from a population.
Santiago Perez‐Lloret +2 more
openaire +3 more sources