Data science and analysis: general

For many organizations data is a by-product, but for the smarter ones it is the heartbeat of their business.

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

Este libro es una guia completa para cualquier persona que desee sumergirse en la programacion de computadoras, independientemente del area o disciplina del conocimiento.

Single-subject research designs have been used to build evidence to the effective treatment of problems across various disciplines including social work, psychology, psychiatry, medicine, allied health fields, juvenile justice, and special education.

Presents the methodology of big data analysis using examples from research and industry There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important.

An updated edition on membrane biology, providing new high resolution structures of membrane proteins and insights into how they function.

Who is most likely to buy and what is the best way to target them?

Statistics in Language Research gives a non-technical but more or less complete treatment of Analysis of Variance (ANOVA) for language researchers.

The approximation and the estimation of nonparametric functions by projections on an orthonormal basis of functions are useful in data analysis.

A year of HBR's essential thinking on techall in one place.

From world-class qualitative experts comes a practical, step-by-step introduction to doing dyadic interviews.

Full of practical advice and real-world examples, this step-by-step guide offers you an accessible introduction to doing quantitative social research using Microsoft Excel.

Discusses methods available for longitudinal data analysis in non-technical language, allowing readers to apply techniques to their work.

L'Union Africaine et certaines organisations comme le NEPAD ont élaboré des politiques pour le développement de l'Afrique jusqu'à ce jour.

This valuable text presents methods and techniques for conducting an animal disease surveillance program, and developing an animal health moitoring system.

The GIS Guide to Public Domain Data gives users of geographic information systems (GIS) relevant information about the sources and quality of available public domain spatial data.

A comprehensive compilation of new developments in data linkage methodology The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage, yet the standard texts on linkage are still those which describe the seminal work from the 1950-60s, with some updates.

Master complex problems and face radical uncertainty by unleashing the power of small data Is your business using data to its optimum potential?

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

Four leading experts convey the promise of data science and examine challenges in achieving its benefits and mitigating some harms.

'Eye-opening.

A user-friendly, introductory, learning-by-doing bridge between classical and machine learning time series analysis with R.

Comprehensive overview of the spectroscopic, mineralogical, and geochemical techniques used in planetary remote sensing.

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

This guidebook is for those who want to use computational experiments to support their work in algorithm design and analysis.

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.