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Cellular phones are now offering an ubiquitous means for scientists to observe life: how people act, move and respond to external influences. They can be utilized as measurement devices of individual persons and for groups of people of the…

Physics and Society · Physics 2015-06-12 Shao-Meng Qin , Hannu Verkasalo , Mikael Mohtaschemi , Tuomo Hartonen , Mikko Alava

From the sampling of data to the initialisation of parameters, randomness is ubiquitous in modern Machine Learning practice. Understanding the statistical fluctuations engendered by the different sources of randomness in prediction is…

Machine Learning · Statistics 2022-10-03 Bruno Loureiro , Cédric Gerbelot , Maria Refinetti , Gabriele Sicuro , Florent Krzakala

We provide methods to validate and compare sensor outputs, or inference algorithms applied to sensor data, by adapting statistical scoring rules. The reported output should either be in the form of a prediction interval or of a parameter…

Data Analysis, Statistics and Probability · Physics 2015-07-07 A. D. Martin , T. C. A. Molteno , M. Parry

Many experiments can be interpreted in terms of random processes operating according to some internal protocols. When experiments are costly or cannot be repeated only one or a few finite samples are available. In this paper we study data…

Data Analysis, Statistics and Probability · Physics 2016-02-02 Marian Kupczynski , Hans De Raedt

The application of machine learning to physics problems is widely found in the scientific literature. Both regression and classification problems are addressed by a large array of techniques that involve learning algorithms. Unfortunately,…

Machine Learning · Computer Science 2022-10-03 Umberto Michelucci , Francesca Venturini

A new class of statistical deformable models is introduced to study high-dimensional curves or images. In addition to the standard measurement error term, these deformable models include an extra error term modeling the individual…

Statistics Theory · Mathematics 2011-08-24 Jérémie Bigot , Benjamin Charlier

In this work, the normal modes of a two-dimensional oscillating system have been studied from a theoretical and experimental point of view. The normal frequencies predicted by the Hessian matrix for a coupled two-dimensional particle system…

The density matrix in quantum mechanics parameterizes the statistical properties of the system under observation, just like a classical probability distribution does for classical systems. The expectation value of observables cannot be…

Quantum Physics · Physics 2014-09-01 K. Temme , F. Verstraete

The mobile acceleration sensor has been used to in Physics experiments on free and damped oscillations. Results for the period, frequency, spring constant and damping constant match very well to measurements obtained by other methods. The…

Research on mobile phone use often starts with a question of "How much time users spend on using their phones?". The question involves an equal-length measure that captures the duration of mobile phone use but does not tackle the other…

Computers and Society · Computer Science 2017-11-28 Jonathan J. H. Zhu , Hexin Chen , Tai-Quan Peng , Xiao Fan Liu , Haixing Dai

Thermodynamic parameters such as temperature and pressure can be defined from the statistical behavior of a system. Therefore, thermal fluctuation is an inseparable characteristic of these parameters which eventually finds its way into…

Computational Physics · Physics 2017-02-28 Alek Bedroya , Mahmud Bahmanabadi

The measurement error with normal distribution is universal in applications. Generally, smaller measurement error requires better instrument and higher test cost. In decision making based on attribute values of objects, we shall select an…

Artificial Intelligence · Computer Science 2013-06-04 Hong Zhao , Fan Min , William Zhu

Biological systems sense and extract information from fluctuating signals while operating under energetic constraints and limited resolution. We introduce a general chemical model in which a sensor, coupled to a signaling pathway activated…

Statistical Mechanics · Physics 2025-12-09 Giorgio Nicoletti , Ivan Di Terlizzi , Daniel Maria Busiello

Acceleration sensors built into smartphones, i-pads or tablets can conveniently be used in the Physics laboratory. By virtue of the equivalence principle, a sensor fixed in a non-inertial reference frame cannot discern between a…

Physics Education · Physics 2016-07-05 Martín Monteiro , Cecilia Cabeza , Arturo C. Martí

Machine learning models are often evaluated using point estimates of performance metrics such as accuracy, F1 score, or mean squared error. Such summaries fail to capture the inherent variability induced by stochastic elements of the…

Machine Learning · Computer Science 2026-05-13 Christoph Lehmann , Yahor Paromau

Measurement error is a pervasive issue which renders the results of an analysis unreliable. The measurement error literature contains numerous correction techniques, which can be broadly divided into those which aim to produce exactly…

Methodology · Statistics 2021-11-08 Dylan Spicker , Michael P Wallace , Grace Y Yi

Typical experimental measurement is set up as a study of the system's response to a stationary external excitation. This approach considers any random fluctuation of the signal as spurious contribution which is to be eliminated via…

A freely available educational application (a mobile website) is presented. This provides access to educational material and drilling on selected topics within mathematics and statistics with an emphasis on tablets and mobile phones. The…

Other Statistics · Statistics 2014-12-10 Jamie Lentin , Anna H. Jonsdottir , David Stern , Victoria Mokua , Gunnar Stefansson

The proper choice of a measurement technique that minimizes systematic and random uncertainty is an essential part of experimental physics. These issues are difficult to teach in the introductory laboratory, though: because most experiments…

Physics Education · Physics 2011-08-26 Chad Orzel , Gary Reich , Jonathan Marr

In this article we present very intuitive, easy to follow, yet mathematically rigorous, approach to the so called data fitting process. Rather than minimizing the distance between measured and simulated data points, we prefer to find such…

Data Analysis, Statistics and Probability · Physics 2017-08-07 Marek W. Gutowski