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Item type:Publication, Statistical tables in Primary Education textbooks of Peru(Facultad de Ciencias de la Educacion, 2022-01-01)In recent years, the literature shows an increase in research analyzing statistical representation of data in textbooks, but in the Peruvian context is still scarce. Therefore, this research aims to analyze activities on statistical tables present in mathematics textbooks, published by the Ministry of Education and distributed free of charge to teachers and students of Primary Education in Peru. The methodology is qualitative and descriptive. For data analysis, the content analysis technique was used by analyzing types of statistical table, types of task, reading levels and semiotic complexity levels as units of analysis in a complete series of mathematics textbooks of Primary Education, from first to sixth grade, one per level, due to their wide national coverage. The results allow us to observe predominance of tally charts and data tables, completion and comparison tasks, reading level 2 (reading within data) and semiotic complexity level 3 (representation of data distribution). It is concluded that it is necessary to increase the number and variety of tasks related to statistical tables proposed in mathematics textbooks, as well as to reinforce the presence of the highest levels of reading and semiotic complexity in the last years of Primary Education in Peru. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Innovating statistics education: The design of a novel app using design thinking(Multidisciplinary Digital Publishing Institute (MDPI), 2024-09-01)Statistical education at university level faces significant challenges, particularly with the rapid advancements in technology and evolving teaching methods. Updating teaching methodologies for statistics in higher education is essential. Information technologies can greatly enhance the learning of statistical content, but many existing platforms are not well-suited for university contexts, either due to language barriers or how the content is presented (often confusing, with limited explanations or lacking context). It is crucial to have a student-centered platform that addresses these issues, ensuring an effective and efficient learning experience. This study introduces “EstApp”, an innovative mobile application prototype designed for teaching and learning descriptive statistics in university courses. The application was developed using the Design Thinking methodology, which emphasizes user experience and focuses on the needs of the end users. The design process involved stages of empathizing, defining, ideating, prototyping, and testing, culminating in validation through user tests with university students and professors. This study concludes that EstApp’s functionalities enhance understanding of (1) statistical models through interactive graphs and data visualizers; (2) probability concepts via a probability calculator; and (3) descriptive statistics through real-time data generation and visualizers. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Electronic voting and invalid votes: evidence from a natural experiment in Peru(Springer Science+Business Media, 2026-01-01)This paper examines the impact of electronic voting in Peru. Our empirical analysis exploits variation from a natural experiment to implement a difference-in-difference strategy. Our estimates indicate that electronic voting reduced the share of invalid votes by almost two-thirds. This reduction appears to be driven by fewer voter errors rather than changes in protest voting. However, in contrast to recent studies, we find no evidence of substantial changes in other electoral outcomes, such as turnout or vote composition. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Bayesian quantile regression models for heavy tailed bounded variables using the No-U-Turn sampler(Springer Science and Business Media Deutschland GmbH, 2025-07-01)When we are interested in knowing how covariates impact different levels of the response variable, quantile regression models can be very useful, with their practical use being benefited from the increasing of computational power. The use of bounded response variables is also very common when there are data containing percentages, rates, or proportions. In this work, with the generalized Gompertz distribution as the baseline distribution, we derive two new two-parameter distributions with bounded support, and new quantile parametric mixed regression models are proposed based on these distributions, which consider bounded response variables with heavy tails. Estimation of the parameters using the Bayesian approach is considered for both models, relying on the No-U-Turn sampler algorithm. The inferential methods can be implemented and then easily used for data analysis. Simulation studies with different quantiles (q=0.1, q=0.5 and q=0.9) and sample sizes (n=100, n=200, n=500, n=2000, n=5000) were conducted for 100 replicas of simulated data for each combination of settings, in the (0, 1) and [0, 1), showing the good performance of the recovery of parameters for the proposed inferential methods and models, which were compared to Beta Rectangular and Kumaraswamy regression models. Furthermore, a dataset on extreme poverty is analyzed using the proposed regression models with fixed and mixed effects. The quantile parametric models proposed in this work are an alternative and complementary modeling tool for the analysis of bounded data.2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Bayesian Calibration of a 2d Hydraulic Model Using a Convolutional Neural Network Emulator(RELX Group (Netherlands), 2025-01-01)6 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Charged-particle multiplicity distributions over a wide pseudorapidity range in p–Pb collisions at √ˢɴɴ=5.02 TeV(Springer Nature, 2025)This paper presents the primary charged-particle multiplicity distributions in proton–lead collisions at a centre-of-mass energy per nucleon–nucleon collision of √ˢɴɴ = 5.02 TeV. The distributions are reported for non-single diffractive collisions in different pseudorapidity ranges. The measurements are performed using the combined information from the Silicon Pixel Detector and the Forward Multiplicity Detector of ALICE. The multiplicity distributions are parametrised with a double negative binomial distribution function which provides satisfactory descriptions of the distributions for all the studied pseudorapidity intervals. The data are compared to models and analysed quantitatively, evaluating the first four moments (mean, standard deviation, skewness, and kurtosis). The shape evolution of the measured multiplicity distributions is studied in terms of KNO variables and it is found that none of the considered models reproduces the measurements. This paper also reports on the average charged-particle multiplicity, normalised by the average number of participating nucleon pairs, as a function of the collision energy. The multiplicity results are then compared to measurements made in proton–proton and nucleus–nucleus collisions across a wide range of collision energies.9