An Introduction to Data Science is an easy-to-read, gentle introduction for advanced undergraduate, certificate, and graduate students coming from a wide range of backgrounds into the world of data ……続きを見る
Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton,focuses on the concepts foundational for students starting a business analytics or data science degree program. T……続きを見る
This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical financ……続きを見る
Maximum Likelihood Estimation with Stata, Fifth Edition is the essential reference and guide for researchers in all disciplines who wish to write maximum likelihood (ML) estimators in Stata. Beyond ……続きを見る
An Introduction to Data Science with Python by Jeffrey S. Saltz and Jeffery M. Stanton provides readers who are new to Python and data science with a step-by-step walkthrough of the tools and techni……続きを見る
This book aims to compile typical fundamental-to-advanced statistical methods to be used for health data sciences. Although the book promotes applications to health and health-related data, the mode……続きを見る
This book is a collection of exercises covering all the main topics in the modern theory of stochastic processes and its applications, including finance, actuarial mathematics, queuing theory, and r……続きを見る
This handbook presents a systematic overview of approaches to, diversity, and problems involved in interdisciplinary rating methodologies. Historically, the purpose of ratings is to achieve informat……続きを見る
