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Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This... Læs mere
Real World Data Analysis shows you how you think about data and the results you want to achieve with it. Author Philipp Janert teaches you how to effectively approach... Læs mere
Originally published in 1971, this text is intended for signals and systems courses which emphasize probability. It provides an introduction to... Læs mere
The critical algorithms used in GIS are notoriously difficult to both teach and understand. This book address the problem by combining rigorous formal language with example case studies and student exercises.
The critical algorithms used in GIS are notoriously difficult to both teach and understand. This book address the problem by combining rigorous formal language with example case studies and student exercises.
Today, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control.
With in-depth descriptions of data analysis techniques both for summarizing and correlation, the author's unconventional approach employs the concept of multivariate data summarization as an alternative to conventional machine-learning prediction methods.
This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students.
This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R.