Contingency tables arise in diverse fields, including life sciences, education, social and political sciences, notably market research and opinion surveys.
Dynamic Time Series Models using R-INLA: An Applied Perspective is the outcome of a joint effort to systematically describe the use of R-INLA for analysing time series and showcasing the code and description by several examples.
Millions of users create and share Excel spreadsheets every day, but few go deeply enough to learn the techniques that will make their work much easier.
Millions of users create and share Excel spreadsheets every day, but few go deeply enough to learn the techniques that will make their work much easier.
Explore essential quantum computing algorithms and master concepts intuitively with minimal math expertise requiredKey FeaturesLearn the fundamentals with an introduction to matrix arithmeticWrite quantum computing programs in Qiskit-IBM's publicly available quantum computing websiteEmail your questions directly to the author-no question is too elementaryPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionNavigate the quantum computing spectrum with this book, bridging the gap between abstract, math-heavy texts and math-avoidant beginner guides.
This book is designed to explain the fundamental principles of automatic control through 20 lessons, each incorporating worked examples and MATLAB(R)-based exercises to help readers effectively understand and apply the proposed methods.
Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote.
Master MATLAB(r) step-by-step The MATLAB-- "e;MATrix LABoratory"e;--computational environment offers a rich set of capabilities to efficiently solve a variety of complex analysis, simulation, and optimization problems.
Balanced coverage of the methodology and theory of numerical methods in finance Numerical Methods in Finance bridges the gap between financial theory and computational practice while helping students and practitioners exploit MATLAB for financial applications.
Praise for RiskGrade Your Investments "e;In the same way that the introduction of RiskMetrics raised the level of the discussion (and sometimes debate) regarding market risk measurement and management at large financial institutions, the introduction of RiskGrades and this book represent a major step in the understanding and application of risk measurement and management techniques by individual investors.
Inspired by the author's need for practical guidance in the processes of data analysis, A Practical Guide to Scientific Data Analysis has been written as a statistical companion for the working scientist.
The fun and easy way to learn to use this leading business intelligence tool Written by an author team who is directly involved with SAS, this easy-to-follow guide is fully updated for the latest release of SAS and covers just what you need to put this popular software to work in your business.
The fun and easy way to learn to use this leading business intelligence tool Written by an author team who is directly involved with SAS, this easy-to-follow guide is fully updated for the latest release of SAS and covers just what you need to put this popular software to work in your business.
SPSS (Statistical Package for the Social Sciences) is a data management and analysis software that allows users to generate solid, decision-making results by performing statistical analysis This book provides just the information needed: installing the software, entering data, setting up calculations, and analyzing data Covers computing cross tabulation, frequencies, descriptive ratios, means, bivariate and partial correlations, linear regression, and much more Explains how to output information into striking charts and graphs For ambitious users, also covers how to program SPSS to take their statistical analysis to the next level
With an emphasis on social science applications, Event History Analysis with R, Second Edition, presents an introduction to survival and event history analysis using real-life examples.
With an emphasis on social science applications, Event History Analysis with R, Second Edition, presents an introduction to survival and event history analysis using real-life examples.
Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data.
Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data.
After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured in recent years, and they are a keystone in large epidemiological studies.
After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured in recent years, and they are a keystone in large epidemiological studies.
Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples.
Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples.
Winner of the 2024 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data.
Winner of the 2024 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data.
Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control and insights on how principles developed earlier can be applied to current and emerging problems.
Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparison problems big and small, with guidance toward error rate control and insights on how principles developed earlier can be applied to current and emerging problems.
