Tag: Statistical

Free Download Trends in Statistical Codicology by Marilena Maniaci
English | PDF,EPUB | 2021 | 780 Pages | ISBN : 3110711427 | 114.9 MB
The application of statistical techniques to the study of manuscript books, based on the analysis of large data sets acquired through the archaeological observation of manuscripts, is one of the most original trends in codicological research, aiming not only to reconstruct on a sound basis the methods and processes used in book manufacture and their tendential evolution in space and time, but also to interpret them as the result of a dynamic interplay between various and often incompatible needs (of cultural, technical, social and economic nature) that book artisans had to reconcile in the best possible way.

Free Download Statistical Thinking: Analyzing Data in an Uncertain World by Russell Poldrack
English | June 20, 2023 | ISBN: 0691250936, 0691218447 | True PDF | 280 pages | 50.5 MB
An essential introduction to statistics for students of psychology and the social sciences

Free Download Statistical Rock Physics
English | 2024 | ISBN: 3031466993 | 550 Pages | PDF EPUB (True) | 29 MB
The book is the first systematic and comprehensive treatise of stochastic models and computational tools that have emerged in rock-physics in the last 20 years. The field of statistical rock-physics is a part of rock-physics (Petrophysics). Its concepts, methods and techniques are borrowed from stochastic geometry and statistical physics. This discipline describes the interior geometry of rocks; derives their effective physical properties based on their random composition and the random arrangement of their constituents; and builds models to simulate the past geological processes that had formed the rock.

Free Download Statistical Models for Nucleon Structure Function
Carlos Alberto Mirez Tarrillo, Luis Augusto Trevisan
English | 2024 | ISBN: 1527568954 | 206 Pages | PDF | 2.92 MB

Free Download Statistical Analysis with R Essentials For Dummies
English | 2024 | ISBN: 1394263422 | 153 Pages | PDF | 3 MB
Statistical Analysis with R Essentials For Dummies is your reference to all the core concepts about R―the widely used, open-source programming language and data analysis tool. This no-nonsense book gets right to the point, eliminating review material, wordy explanations, and fluff. Understand all you need to know about the foundations of R, swiftly and clearly. Perfect for a brush-up on the basics or as an everyday desk reference on the job, this is the reliable little book you can always turn to for answers.

Free Download Model-Based Monitoring and Statistical Control
English | 2024 | ISBN: 1032550120 | 318 Pages | PDF (True) | 10 MB
Available in English for the first time, this classic and influential book by the late Kohei Ohtsu presents real examples of ships in motion under irregular ocean waves, how to understand the characteristics of fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling. It also explains how to realize prediction and optimal control based on time series models.

Free Download Mathematical and Statistical Approaches for Anaerobic Digestion Feedstock Optimization by Federico Moretta , Giulia Bozzano
English | PDF EPUB (True) | 2024 | 75 Pages | ISBN : 3031564596 | 7.8 MB
This book examines biomass mixture modeling and optimization.

Free Download M-statistics: Optimal Statistical Inference for a Small Sample by Eugene Demidenko
English | August 22, 2023 | ISBN: 1119891795 | 240 pages | MOBI | 17 Mb
M-STATISTICS A comprehensive resource providing new statistical methodologies and demonstrating how new approaches work for applications M-statistics introduces a new approach to statistical inference, redesigning the fundamentals of statistics, and improving on the classical methods we already use. This book targets exact optimal statistical inference for a small sample under one methodological umbrella. Two competing approaches are maximum concentration (MC) and mode (MO) statistics combined under one methodological umbrella, which is why the symbolic equation M=MC+MO. M-statistics defines an estimator as the limit point of the MC or MO exact optimal confidence interval when the confidence level approaches zero, the MC and MO estimator, respectively. Neither mean nor variance plays a role in M-statistics theory. Novel statistical methodologies in the form of double-sided unbiased and short confidence intervals and tests apply to major statistical Our new developments are accompanied by respective algorithms and R codes, available at GitHub, and as such readily available for applications. M-statistics is suitable for professionals and students alike. It is highly useful for theoretical statisticians and teachers, researchers, and data science analysts as an alternative to classical and approximate statistical inference.

Free Download Introduction to Probability, Statistical Methods, Design of Experiments and Statistical Quality Control
English | 2024 | ISBN: 9819993628 | 637 Pages | PDF EPUB (True) | 70 MB
This revised book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments, and statistical quality control. It is shaped by the experience of the two teachers teaching statistical methods and concepts to engineering students. Practical examples and end-of-chapter exercises are the highlights of the text, as they are purposely selected from different fields. Statistical principles discussed in the book have a great relevance in several disciplines like economics, commerce, engineering, medicine, health care, agriculture, biochemistry, and textiles to mention a few.

Free Download Information Criteria and Statistical Modeling by Sadanori Konishi , Genshiro Kitagawa
English | PDF(True) | 2008 | 282 Pages | ISBN : 0387718869 | 5.4 MB
The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.