Results 21 to 30 of about 419,428 (264)
Public Health and Toxicology, 2021 Null hypothesis significance testing (NHST) text was once widely popular and almost systematically used for the identification of causal relations and for risk assessment in toxicology and medicine.
Silvio Roberto Vinceti +1 more
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Statistical Hypothesis Testing Based on Machine Learning: Large Deviations Analysis
IEEE Open Journal of Signal Processing, 2022 We study the performance of Machine Learning (ML) classification techniques. Leveraging the theory of large deviations, we provide the mathematical conditions for a ML classifier to exhibit error probabilities that vanish exponentially, say $\exp (-n\,I)$
Paolo Braca +5 more
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Discrete convolution statistic for hypothesis testing [PDF]
Communications in Statistics - Theory and Methods, 2020 The question of testing for equality in distribution between two linear models, each consisting of sums of distinct discrete independent random variables with unequal numbers of observations, has emerged from the biological research. In this case, the computation of classical $ ^2$ statistics, which would not include all observations, results in loss ...
Giulio Prevedello, Ken R. Duffy
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Statistical analysis of control quality of MPC using testing hypothesis [PDF]
MATEC Web of Conferences, 2019 Methods of the statistical induction have a significant role in the quantitative research. In a wide spectrum of research areas, the methods based on testing hypotheses have been frequently used.
Kubalcik Marek +2 more
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A Fuzzy Take on the Logical Issues of Statistical Hypothesis Testing
Philosophies, 2021 Statistical Hypothesis Testing (SHT) is a class of inference methods whereby one makes use of empirical data to test a hypothesis and often emit a judgment about whether to reject it or not. In this paper, we focus on the logical aspect of this strategy,
Matthew Booth, Fabien Paillusson
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Statistical inference: Hypothesis testing
Allergologia et Immunopathologia, 2010 The aim of statistical inference is to predict the parameters of a population, based on a sample of data. Inferential statistics encompasses the estimation of parameters and model predictions. The present article describes the hypothesis tests or statistical significance tests most commonly used in healthcare research.
S. Pérez-Vicente +2 more
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A logical analysis of null hypothesis significance testing using popular terminology
BMC Medical Research Methodology, 2022 Background Null Hypothesis Significance Testing (NHST) has been well criticised over the years yet remains a pillar of statistical inference. Although NHST is well described in terms of statistical models, most textbooks for non-statisticians present the
Richard McNulty
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Interpreting "statistical hypothesis testing" results in clinical research
Journal of Ayurveda and Integrative Medicine, 2012 Difference between "Clinical Significance and Statistical Significance" should be kept in mind while interpreting "statistical hypothesis testing" results in clinical research.
Sanjeev B Sarmukaddam
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OS-PCA: Orthogonal Smoothed Principal Component Analysis Applied to Metabolome Data
Metabolites, 2021 Principal component analysis (PCA) has been widely used in metabolomics. However, it is not always possible to detect phenotype-associated principal component (PC) scores.
Hiroyuki Yamamoto +2 more
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Hypothesis-testing-based Range Statistical Resolution Limit of Radar
Leida xuebao, 2019 Resolution performance is an important performance criteria of the radar systems. Typically, the Ambiguity Function (AF) of signals is used to define the range and Doppler limits. In this study Some new opinions are proposed—First, the AF is based on the
ZHANG Yunlei, TANG Jun, WANG Li
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