CLINICAL-STATISTICAL STUDY ON THE FREQUENCY OF WISDOM TOOTH INCLUSION PATHOLOGY by Dorin Ioan Cocoș, Eugen Bud, Mariana Păcurar, Carmen Galea, Calin Alina, Kamel Earar

“…Including wisdom teeth is a common problem in dental practice, associated with significant complications such as gum inflammation, caries, root resorption of neighboring teeth, and cyst formation. This clinical-statistical study analyzed the frequency and distribution of wisdom tooth inclusion pathology according to age and anatomical location, within a group of 50 patients aged between 19 and 65 years, divided into five age categories. …”
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Exploring Students’ Numerical Literacy on Statistical Problem-Solving in Indonesia by Ika Santia, Aprilia Dwi Handayani

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Non-linear development in statistical learning of visual orthographic regularities by Rujun Duan, Qi Sun, Xiuhong Tong

“…Abstract Statistical learning is a core ability for individuals in extracting and integrating regularities and patterns from linguistic input. …”
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The automatization of press statistics as one of the ways to improve the service of information users by Angelė Šarlauskienė

“…The Department of Press Statistics functions independently as a constituent part of the automatization of press statistics in the Book Palace. …”
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Research for SARIMA and PatchTSMixer Models on the IEA Monthly Statistics Dataset by Hu Yuwei

“…This study aims to address this gap by evaluating and comparing the prediction accuracy of machine learning and deep learning techniques using the Monthly Electricity Statistics dataset from the International Energy Agency (IEA). …”
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Extreme Event Statistics in Dst, SYM‐H, and SMR Geomagnetic Indices by A. Bergin, S. C. Chapman, N. W. Watkins, N. R. Moloney, J. W. Gjerloev

“…The Dst index ring‐current monitor, derived from an hourly average over four low‐latitude stations, is a benchmark for extreme space weather events, and has been extensively studied statistically. We apply extreme value theory (EVT) to two geomagnetic ring current indices: SYM‐H (derived from 6 stations) and SMR (derived from up to 120 stations). …”
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Inferential Statistics from Black Hispanic Breast Cancer Survival Data by Hafiz M. R. Khan, Anshul Saxena, Elizabeth Ross, Venkataraghavan Ramamoorthy, Diana Sheehan

“…In this paper we test the statistical probability models for breast cancer survival data for race and ethnicity. …”
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Self-Normalized Moderate Deviations for Degenerate <i>U</i>-Statistics by Lin Ge, Hailin Sang, Qi-Man Shao

Subjects: “…degenerate <i>U</i>-statistics…”
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Exploring the Potential of Neural Networks to Predict Statistics of Solar Wind Turbulence by Daniel Wrench, Tulasi N. Parashar, Ritesh K. Singh, Marcus Frean, Ramesh Rayudu

“…Here, we study the utility of artificial neural networks (ANNs) to predict statistics of sparse time series. Our focus is not on time series prediction but on gleaning the best possible information about the statistical behavior of the system. …”
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Income shifting by multinational enterprises as a source of mismeasurement in aggregate statistics by Serena Fatica, Wildmer Daniel Gregori

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The Empirical Cressie-Read Test Statistics for Longitudinal Generalized Linear Models by Junhua Zhang, Ruiqin Tian, Suigen Yang, Sanying Feng

“…The ECR test statistic includes empirical likelihood as a special case. …”
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Regional Economic Development of the PRC through the Data of the World Economic Statistics by Andrei V. Ostrovskii

“…These results are compared with data from various countries in terms of gross domestic product (GDP) and GDP per capita. Based on statistical data from the National Bureau of Statistics (NBS) of China for 2022, it was determined that China’s GDP ranks first globally in terms of purchasing power parity (PPP) and second in terms of the dollar exchange rate. …”
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Signal Nonstationary Degree Evaluation Method Based on Moving Statistics Theory by Haoxiang He, Shitao Cheng, Xiaofu Zhang

“…Nonstationary signal refers to the signal whose statistics change with time, and its nonstationary degree evaluation can provide effective support for the evaluation of the operating state of the signal source. …”
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Scaling Analysis of the Tensile Strength of Bamboo Fibers Using Weibull Statistics by Jiaxing Shao, Fang Wang, Lu Li, Junqian Zhang

“…The size effects in fiber length on the strength were analyzed based on Weibull statistics. The results verify the use of Weibull parameters from specimen testing for predicting the strength distributions of fibers of longer gauge lengths.…”
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Second-Order Moment Convergence Rates for Spectral Statistics of Random Matrices by Junshan Xie

“…This paper considers the precise asymptotics of the spectral statistics of random matrices. Following the ideas of Gut and Spătaru (2000) and Liu and Lin (2006) on the precise asymptotics of i.i.d. random variables in the context of the complete convergence and the second-order moment convergence, respectively, we will establish the precise second-order moment convergence rates of a type of series constructed by the spectral statistics of Wigner matrices or sample covariance matrices.…”
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Constitutive Model of Rock Uniaxial Damage Based on Rock Strength Statistics by Ming Ji, Kai Chen, Hong Jun Guo

“…Based on the assumption that rock strength follows the log normal distribution statistically, this paper establishes a damage constitutive model of rock under uniaxial stress conditions in combination with the Mohr–Coulomb strength criterion and damage mechanical theory. …”
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Comparing circular and flexibly-shaped scan statistics for disease clustering detection by Lina Wang, Xiang Li, Zhengbin Zhang, Haoxun Yuan, Pengfei Lu, Yaru Li

Subjects: “…spatial scan statistics…”
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Computing the Performance Measures in Queueing Models via the Method of Order Statistics by Yousry H. Abdelkader, Maram Al-Wohaibi

“…These measures depend on the moments of order statistics. The expected value and the variance of the maximum (minimum) number of customers in the system as well as the expected value and the variance of the minimum (maximum) waiting time are presented. …”
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Edge Statistics for Lozenge Tilings of Polygons, II: Airy Line Ensemble by Amol Aggarwal, Jiaoyang Huang

“…We show that the edge statistics around any point on the arctic boundary, that is not a cusp or tangency location, converge to the Airy line ensemble. …”
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