Data science and analysis: general

A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.

A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.

Connects fundamental mathematical theory with real-world problems, through efficient and scalable optimization algorithms.

Shows how comparative ethnographic methods can be successfully used to study important human concerns in anthropology.

How best to interpret and apply geochemical data to understand geological processes, for graduate students, researchers, and professionals.

Providing clear, practical explanations of research methods in business studies, this guide is indispensable for students writing reports.

Providing clear, practical explanations of research methods in business studies, this guide is indispensable for students writing reports.

How best to interpret and apply geochemical data to understand geological processes, for graduate students, researchers, and professionals.

A wide-ranging discussion of factors that impede the cumulation of knowledge in the social sciences, with suggested solutions.

This is the first comprehensive overview of the exciting field of the ''science of science''.

A methodological toolkit for social scientists to create their own infrastructure for collecting and analyzing social media big data.

A methodological toolkit for social scientists to create their own infrastructure for collecting and analyzing social media big data.

Textbook that uses examples and Jupyter notebooks from across the sciences and engineering to teach Python programming.

Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.

Textbook for students and researchers in oceanography and Earth science on theory and practice of time series analysis using MATLAB.

Provides thorough and comprehensive coverage of new and important quantitative methods in data science, for graduate students and practitioners.

It humanizes high-level debates over indicators and data in development aid, showing how they are used to make life-or-death decisions.

This book addresses common questions from HCI researchers when trying to do statistical analysis on their data.

Presents an analysis and visualization of social networks integrating theory, applications, and professional software for performing network analysis (Pajek).

Analyzes scale effects across a range of political dimensions, encompassing different political levels using a multi-method approach.

Analyzes scale effects across a range of political dimensions, encompassing different political levels using a multi-method approach.

Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.

Displays the broad range of quantitative approaches to analysing ecological networks, providing clear examples and guidance for researchers.

Provides thorough and comprehensive coverage of new and important quantitative methods in data science, for graduate students and practitioners.

This book addresses common questions from HCI researchers when trying to do statistical analysis on their data.

Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students.

A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.

Surveys major topics in the epistemology of big data based scientific approaches and defends an inductivist view of these approaches.

Textbook for students and researchers in oceanography and Earth science on theory and practice of time series analysis using MATLAB.

Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students.

This is the first comprehensive overview of the exciting field of the ''science of science''.

Presents an analysis and visualization of social networks integrating theory, applications, and professional software for performing network analysis (Pajek).

It humanizes high-level debates over indicators and data in development aid, showing how they are used to make life-or-death decisions.

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.

This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.

Management research is criticised for poor research practices and not addressing important problems.

This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

Management research is criticised for poor research practices and not addressing important problems.

Examines a set of voter information campaigns worldwide to assess their effectiveness, and develops a new social science research model aimed at cumulative learning.

Examines a set of voter information campaigns worldwide to assess their effectiveness, and develops a new social science research model aimed at cumulative learning.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.

Employs basic mathematical skills to teach students how to address topical, real-world problems using quantitative reasoning.

A rigorous introduction to geometric and topological inference, for anyone interested in a geometric approach to data science.

Employs basic mathematical skills to teach students how to address topical, real-world problems using quantitative reasoning.