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.
A hands-on lab guide in the MATLAB programming language that enables students in the life sciences to reason quantitatively about living systems across scalesThis lab guide accompanies the textbook Quantitative Biosciences, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems.
A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "e;language"e; of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods.
Tools from macroeconomics and finance to incorporate the central role that data plays in the economyThe most valuable firms in the global economy are valued largely for their data.
Electronic Health Records (EHR) are longitudinal data that are stored in a database that captures current and new patients at different points in time.
An ideal textbook for complete beginnersteaches from scratch R, statistics, and the fundamentals of quantitative social scienceData Analysis for Social Science provides a friendly introduction to the statistical concepts and programming skills needed to conduct and evaluate social scientific studies.
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.
SHORTLISTED: Business Book Awards 2025 - People, Culture & ManagementOrganizations often start their data journey by either procuring the technology or hiring the people.
'A statistical national treasure' Jeremy Vine, BBC Radio 2'Required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics.
This volume highlights the ways in which recent developments in corpus linguistics and natural language processing can engage with topics across language studies, humanities and social science disciplines.
The research landscape is changing, with key global research funders now requiring institutions to demonstrate how they will preserve and share research data.
An insider's guide to data librarianship packed full of practical examples and advice for any library and information professional learning to deal with data.
Spatial Data Science will show GIS scientists and practitioners how to add and use new analytical methods from data science in their existing GIS platforms.
A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.
This book is a collection of empirical and theoretical research papers regarding "Current Issues in Accounting" written by researchers from several different universities.