This is an introduction for social science students to the growing field of spatial data analysis using the R platform. The text assumes no prior knowledge of either, beyond the contents of an introductory statistics course. It uses the open-sourc...Loe edasi...
The ever-expanding availability of spatial data continues to revolutionise research. This book is your go-to guide to getting the most out of handling, mapping and analysing location-based data.Without assuming prior knowledge of GIS, geoco...Loe edasi...
The accessible and student-friendly how to for anyone using R for the first time to analyse location-based data. The ever-expanding availability of spatial data continues to revolutionise research. This book is your go-to guide to...Loe edasi...
(Ilmumisaeg: 15-Apr-2025, Hardback, Kirjastus: John Wiley & Sons Inc, ISBN-13: 9781119872351)
A practical guide to reproducible and high impact mass spectrometry data analysis R Programming for Mass Spectrometry teaches a rigorous and detailed approach to analyzing mass spectrometry data using the R programming language. I...Loe edasi...
This book is a guide to statistical genetics analyses with R. The focus will be on conveying concepts and theories, while providing easy-to-reproduce working examples using established methods and packages. The audience is primarily users without...Loe edasi...
This book focuses on correlation coefficients and its applications in applied science fields. The book begins by describing the historical development and various types of correlations. Rank correlation methods including Pearson’s, Spearman’s, an...Loe edasi...
(Ilmumisaeg: 06-Mar-2025, Hardback, Kirjastus: Springer International Publishing AG, ISBN-13: 9783031780691)
This comprehensive textbook equips students of economics and business, as well as industry professionals, with essential principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Through r...Loe edasi...
Data-driven decision-making is a fundamental component of business success. Use this textbook to learn the core knowledge and techniques for analyzing business data with Python programming.Business Analytics with Python ...Loe edasi...
Data-driven decision-making is a fundamental component of business success. Use this textbook to learn the core knowledge and techniques for analyzing business data with Python programming.Business Analytics with Python ...Loe edasi...
This book comprehensively covers various causal mediation analysis (CMA) methods developed across multiple fields, organizing them into a reader-friendly progression of methodological advancements. Interest in the mechanisms that form causal relat...Loe edasi...
Deriving business value from analytics is a challenging process. Turning data into information requires a business analyst who is adept at multiple technologies including databases, programming tools, and commercial analytics tools. This practical...Loe edasi...
Introduction to Regression Methods for Public Health Using R teaches regression methods for continuous, binary, ordinal, and time-to-event outcomes using R as a tool. Regression is a useful tool for understanding the associations between an...Loe edasi...
This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (“latent”) variables. Although the focus is on simple R code, the book pr...Loe edasi...
This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (“latent”) variables. Although the focus is on simple R code, the book pr...Loe edasi...
(Ilmumisaeg: 10-Dec-2024, Hardback, Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K, ISBN-13: 9783662700730)
This standard work on statistical methods in life sciences and medicine provides easily understandable, illustrative, and practical guidance to students, lecturers and practitioners alike, covering all necessary methods for targeted and careful data...Loe edasi...
Classification problems are common in business, medicine, science, engineering and other sectors of the economy. Data scientists and machine learning professionals solve these problems through the use of classifiers. Choosing one of these data dri...Loe edasi...
