This innovative textbook presents material for a course on modern statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting resear……続きを見る
著者:John D. Levendis
出版社: Springer International Publishing
発売日: 2019年02月02日
In this book, the author rejects the theorem-proof approach as much as possible, and emphasize the practical application of econometrics. They show with examples how to calculate and interpret the n……続きを見る
著者:Vaclav Smil
出版社: Penguin Publishing Group
発売日: 2021年05月04日
**"Vaclav Smil is my favorite author… Numbers Don't Lie takes everything that makes his writing great and boils it down into an easy-to-read format. I unabashedly recommend this book to anyone who l……続きを見る
著者:Faith A. Morrison
出版社: Cambridge University Press
発売日: 2020年12月31日
Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various ……続きを見る
The ideal review for your probability and statistics course
More than 40 million students have trusted Schaum’s Outlines for their expert knowledge and helpful solved problems. Written by renowned e……続きを見る
With contributions from some of the top academics and scientists in the field, Advanced Studies in Multi-Criteria Decision Making presents an updated view of the landscape of Decision Sciences, curr……続きを見る
Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of inte……続きを見る
Introduction to the Theory of Optimization in Euclidean Space is intended to provide students with a robust introduction to optimization in Euclidean space, demonstrating the theoretical aspects of ……続きを見る
著者:Jack Shostak
出版社: SAS Institute
発売日: 2014年03月01日
This comprehensive resource provides on-the-job training for statistical programmers who use SAS in the pharmaceutical industry This one-stop resource offers a complete review of what entry- to inte……続きを見る
A nontechnical guide to the basic ideas of modern causal inference, with illustrations from health, the economy, and public policy.
Which of two antiviral drugs does the most to save people infected……続きを見る
Group representation theory is both elegant and practical, with important applications to quantum mechanics, spectroscopy, crystallography, and other fields in the physical sciences. This book offer……続きを見る
著者:E. T. Jaynes
出版社: Cambridge University Press
発売日: 2015年11月10日
The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical……続きを見る
A systematic, innovative introduction to the field of network analysis, Network Psychometrics with R: A Guide for Behavioral and Social Scientists provides a comprehensive overview of and guide to b……続きを見る
Why mathematical models are so often wrong, and how we can make better decisions by accepting their limits
Whether we are worried about the spread of COVID-19 or making a corporate budget, we depend……続きを見る
Introduction to Chemical Graph Theory is a concise introduction to the main topics and techniques in chemical graph theory, specifically the theory of topological indices. These include distance-bas……続きを見る
An accessible introduction to constructing and interpreting Bayesian models of perceptual decision-making and action.
Many forms of perception and action can be mathematically modeled as probabilist……続きを見る
This book is dedicated to the mathematical study of two-dimensional statistical hydrodynamics and turbulence, described by the 2D Navier–Stokes system with a random force. The authors' main goal is ……続きを見る
Solve SEO problems using data science. This hands-on book is packed with Python code and data science techniques to help you generate data-driven recommendations and automate the SEO workload.
This ……続きを見る
This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation ma……続きを見る
著者:Tim Harford
出版社: Little, Brown Book Group
発売日: 2020年09月17日
The Sunday Times Bestseller
'Tim Harford is one of my favourite writers in the world. His storytelling is gripping but never overdone, his intellectual honesty is rare and inspiring, and his ability……続きを見る
Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. E……続きを見る
Conveniently grouping methods by techniques, such as chi-squared and empirical distributionfunction , and also collecting methods of testing for specific famous distributions, this usefulreference i……続きを見る
This book introduces the point cloud; its applications in industry, and the most frequently used datasets. It mainly focuses on three computer vision tasks -- point cloud classification, segmentatio……続きを見る
Praise for Common Errors in Statistics (and How to Avoid Them)
"A very engaging and valuable book for all who use statistics in any setting."
-CHOICE
"Addresses popular mistakes often made in data c……続きを見る
Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve probl……続きを見る
出版社: Springer International Publishing
発売日: 2020年09月21日
This book proposes new control and protection schemes to improve the overall stability and security of future wide-area power systems. It focuses on the high penetration levels of renewable energy s……続きを見る
出版社: Springer International Publishing
発売日: 2016年11月05日
Current research results in stochastic and deterministic global optimization including single and multiple objectives are explored and presented in this book by leading specialists from various fiel……続きを見る
Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously ou……続きを見る
著者:Alan D. Chave
出版社: Cambridge University Press
発売日: 2017年08月31日
Based on a course taught by the author, this book combines the theoretical underpinnings of statistics with the practical analysis of Earth sciences data using MATLAB. The book is organized to intro……続きを見る
著者:David Williams
出版社: Cambridge University Press
発売日: 2015年11月10日
Probability theory is nowadays applied in a huge variety of fields including physics, engineering, biology, economics and the social sciences. This book is a modern, lively and rigorous account whic……続きを見る