Behavioral Data Analysis With R And Python
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Behavioral Data Analysis with R and Python
Most of the data that companies collect is related to customer behaviors, such as clicks on a website or purchases in a supermarket. But data science algorithms and predictive analytics tools aren't that specific, so customer data is treated the same way as, for example, astronomical or genomic data. This practical guide introduces powerful methods for behavioral data analysis that you're probably not aware of. Advanced experimental design will help you get the most out of your A/B tests, while causal diagrams will allow you to tease out causality from correlation even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, this practical book provides complete examples and exercises in R and Python to help you gain more insight from your data-immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way.
Behavioral Data Analysis with R and Python
Most of the data that companies collect is related to customer behaviors, such as clicks on a website or purchases in a supermarket. But data science algorithms and predictive analytics tools aren't that specific, so customer data is treated the same way as, for example, astronomical or genomic data. This practical guide introduces powerful methods for behavioral data analysis that you're probably not aware of. Advanced experimental design will help you get the most out of your A/B tests, while causal diagrams will allow you to tease out causality from correlation even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, this practical book provides complete examples and exercises in R and Python to help you gain more insight from your immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way
The Power of Complex Systems
This book offers a visionary and interdisciplinary framework for rethinking mobile communication networks through the lens of complex systems. It combines theoretical rigor with real-world relevance, integrating network science, bio-inspired computation and modeling approach, and social behavior to model and design future-proof infrastructures. The innovative approach lies in merging multilayer and higher-order topologies with artificial intelligence and behavioral dynamics, enabling systems that are adaptive, resilient, and socially aware. The book emphasizes the mutual feedback between technological design and human interactions. It addresses researchers, engineers, and policymakers engaged in 6G, digital health, smart cities, and sustainability, offering practical insights into designing intelligent, human-centric, and ethically aligned networks for a hyperconnected future.