Results 11 to 20 of about 14,713,155 (294)
Hypothesis testing, type I and type II errors
Industrial Psychiatry Journal, 2009 Hypothesis testing is an important activity of empirical research and evidence-based medicine. A well worked up hypothesis is half the answer to the research question.
Amitav Banerjee +4 more
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Statistical hypothesis testing: general approach in medical research
Сеченовский вестник, 2021 Statistical hypothesis testing is one of the key steps in modern medical research. Initially, scientists formulate a research hypothesis based on which the statistical hypothesis is then developed and statistically tested.
A. Yu. Suvorov +6 more
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Methods for nonparametric statistics in scientific research. Overview. Part 2
Теория и практика переработки мяса, 2022 The use of nonparametric methods in scientific research provides a number of advantages. The most important of these advantages are versatility and a wide range of such methods.
M. A. Nikitina, I. M. Chernukha
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Scientific African, 2022 In numerous investigations, whether practical or theoretical, a requirement for the Analysis of Variance (ANOVA), is that the variances of the measured groups are equal.
B. Odoi +3 more
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What is the proper way to apply the multiple comparison test? [PDF]
Korean Journal of Anesthesiology, 2018 Multiple comparisons tests (MCTs) are performed several times on the mean of experimental conditions. When the null hypothesis is rejected in a validation, MCTs are performed when certain experimental conditions have a statistically significant mean ...
Sangseok Lee, Dong Kyu Lee
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, 2022 Type-I error rates of tests for different values of K and n.
Kwun Chuen Gary Chan (3641947) +3 more
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COMPARISON OF TRADITIONAL AND MACHINE LEARNING BASE METHODS FOR GROUND POINT CLOUD LABELING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Today, a variety of methods have been proposed by researchers to distinguish ground and non-ground points in point cloud data. Most fully automated methods have a common disadvantage which is the lack of proper algorithm response for all areas and levels
S. M. Ayazi, M. Saadat Seresht
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FULLY CONVOLUTIONAL NETWORKS FOR GROUND CLASSIFICATION FROM LIDAR POINT CLOUDS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied.
A. Rizaldy +3 more
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Statistical and Type II Error Assessment of a Runoff Predictive Model in Peninsula Malaysia
Mathematics, 2021 Flood related disasters continue to threaten mankind despite preventative efforts in technological advancement. Since 1954, the Soil Conservation Services (SCS) Curve Number (CN0.2) rainfall-runoff model has been widely used but reportedly produced ...
Lloyd Ling +2 more
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Journal of Human Environmental Studies, 2008 In a recent article, Killeen (2005) proposed the statistic prep, the probability of replicating an effect, as an alternative to traditional null-hypotheses significant tests (NHST).
Manabu Ichihara +5 more
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