Data science and analysis: general

A complete and comprehensive collaboration providing insight on future approaches to telephone survey methodology Over the past fifteen years, advances in technology have transformed the field of survey methodology, from how interviews are conducted to the management and analysis of compiled data.

What is the true human cost of the war in Afghanistan?

Explore how market valuation must abandon linearity to deliver efficient resource allocation.

This book provides a computational and algorithmic foundation for techniques in topological data analysis, with examples and exercises.

What is Big Data, and why should you care?

Companies used to rely on human experts and their years of experience to guide them.

This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.

WINNER: International Book Awards 2023 - Business: Technology (1st edition) Not everyone needs to be a data scientist, but everyone should be data literate in a fast-moving world that brings new technological developments every day.

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis.

The importance of data analytics is well known, but how can you get end users to engage with analytics and business intelligence (BI) when adoption of new technology can be frustratingly slow or may not happen at all?

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

Become an expert at using Python for advanced statistical analysis of data using real-world examplesAbout This BookClean, format, and explore data using graphical and numerical summariesLeverage the IPython environment to efficiently analyze data with PythonPacked with easy-to-follow examples to develop advanced computational skills for the analysis of complex dataWho This Book Is ForIf you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you.

A clear easy-to-read guide to presenting your message using statistical data Poor presentation of data is everywhere; basic principles are forgotten or ignored.

FINALIST: Next Generation Indie Book Awards 2024 - Education/Academic Non-FictionBe Data Analytical is the book organizations and individuals need to understand how to truly use analytics to turn data into valuable insights and drive smarter decision making.

The aim of this dissertation was to examine two so far separately considered complex constructs, fatigue and mental health, concerning a target group that has to cope with high stress, extraordinary workload, high risks and responsibility: professional pilots.

A comprehensive guide to data analysis techniques for the physical sciences including probability, statistics, data reconstruction, data correction and Monte Carlo methods.

An engaging introduction to data science that emphasizes critical thinking over statistical techniquesAn introduction to data science or statistics shouldn't involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize.

Many librarians' job responsibilities increasingly require them to understand and handle data.

Data Alchemy in the Insurance Industry: The Transformative Power of Big Data Analytics is a groundbreaking work that explores the transformative power of big data analytics within the insurance industry.

Digital heritage can mean many things, from building a database on Egyptian textiles to interacting with family historians over Facebook.

Social tagging (including hashtags) is used over platforms such as Twitter, Facebook, Instagram, Pinterest, WordPress, Tumblr and YouTube across countries and cultures meaning that one single hashtag can link information from a variety of resources.

Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining.

Organize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team.

Data science methods and tools-including programming, data management, visualization, and machine learning-and their application to neuroimaging researchAs neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage, and analyze datasets at unprecedented scales.

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

Rigorous treatment of the theory of deep learning from first principles, with applications to beautiful problems in the natural sciences.

Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field.

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

The social sciences are becoming datafied.

Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining.

A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.

This book is intended for anyone interested in learning more about how search works and how it is evaluated.

This accessible new textbook offers a straightforward introduction to doing spatial statistics.

The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science.