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Fundamentals Of Causal Inference: With R (Chapman Hall/CRC Texts In Statistical Science)

Jese Leos
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Delve into a Vast Repository of Cutting-Edge Statistical Knowledge

The world of statistics is constantly evolving, unveiling groundbreaking techniques and profound insights. If you're an intrepid explorer of this fascinating field, eager to expand your horizons in advanced statistical methods, then the Chapman & Hall/CRC Texts in Statistical Science series is your invaluable roadmap.

Comprehensive Coverage of Statistical Subdisciplines

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  • Bayesian Analysis
  • Biostatistics
  • Data Mining
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  • Nonparametric Statistics
  • Statistical Computing
  • Survival Analysis

Authored by Renowned Statistical Luminaries

The authors behind these texts are esteemed statisticians, renowned for their seminal contributions to the field. Their expertise ensures that every volume is a repository of cutting-edge knowledge, presented with unparalleled clarity and rigor.

Fundamentals of Causal Inference: With R (Chapman Hall/CRC Texts in Statistical Science)
Fundamentals of Causal Inference: With R (Chapman & Hall/CRC Texts in Statistical Science)
by Babette A. Brumback

4.2 out of 5

Language : English
File size : 11937 KB

Rigorous Yet Accessible Approach

While these texts delve into advanced statistical concepts, their pedagogical approach is meticulously designed to make them accessible to students, researchers, and practitioners alike. Detailed explanations, illustrative examples, and comprehensive exercises guide readers through complex methodologies with ease.

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A Librarian's Dream: Comprehensive Resource for Statistical Research

For librarians, the Chapman & Hall/CRC Texts in Statistical Science series is a treasure trove of knowledge. Its comprehensive coverage and authoritative content make it an indispensable resource for academic and research libraries, providing patrons with access to the most up-to-date statistical methodologies.

Invest in Your Statistical Future

Investing in the Chapman & Hall/CRC Texts in Statistical Science series is an investment in your statistical prowess. Each volume is meticulously designed to provide an unparalleled foundation in advanced statistical methods, empowering you to excel in your research, professional endeavors, and pursuit of knowledge.

Call to Action

Unlock the transformative power of advanced statistics today. Browse our extensive collection of Chapman & Hall/CRC Texts in Statistical Science and choose the volumes that align with your statistical aspirations. Embark on a journey that will redefine your understanding of the complexities of data and equip you with the tools to make informed decisions.

Featured Volumes:

Bayesian Analysis

  • "Bayesian Analysis of Stochastic Process Models" by John Kalbfleisch
  • "Bayesian Methods for Data Analysis" by Richard Gelman, Andrew Hill, and Masanao Aihara
  • "Bayesian Networks and Bayesian Logic" by David Heckerman

Biostatistics

  • "Statistical Methods in Cancer Research, Volume 1: Design and Analysis of Clinical Trials" by Mary Gray
  • "Biostatistics: A Bayesian " by John Ibrahim and Michael Chen
  • "Statistical Methods for Health Sciences" by John Rice

Data Mining

  • "Data Mining: Concepts and Techniques, Second Edition" by Jiawei Han, Jian Pei, and Micheline Kamber
  • " to Statistical Learning" by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
  • "Machine Learning: An Algorithmic Perspective" by Stephen Marsland

Econometrics

  • "Econometric Analysis of Cross Section and Panel Data, Second Edition" by Jeffrey Wooldridge
  • "Time Series Econometrics: Advanced Time Series Analysis, Volume 2" by Torben Andersen
  • "Microeconometrics: Methods and Applications" by Cameron and Trivedi

Machine Learning

  • "Machine Learning: A Probabilistic Perspective" by Kevin Murphy
  • "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
  • "Reinforcement Learning: An " by Richard Sutton and Andrew Barto

Nonparametric Statistics

  • "Nonparametric Statistical Methods, Third Edition" by Myles Hollander and Douglas Wolfe
  • "Distribution-Free Statistical Methods, Second Edition" by Robert Hogg and Stephen K. Lenth
  • "Asymptotic Theory of Nonparametric Tests, Second Edition" by J. Hájek

Statistical Computing

  • "Statistical Computing with R" by Maria L. Rizzo
  • "Modern Applied Statistics with S-PLUS, Fourth Edition" by W.N. Venables and B.D. Ripley
  • "The Book of R: A First Course in Statistical Programming with R" by Tilman M. Davies

Survival Analysis

  • "Survival Analysis: A Self-Learning Text, Third Edition" by John Klein and Melvin Moeschberger
  • "Statistical Methods for Lifetime Data, Third Edition" by Jerald Lawless
  • "Survival Analysis Using S: Analysis of Time-to-Event Data, Second Edition" by David Machin, Ying Chen, and Colin Parmar

Fundamentals of Causal Inference: With R (Chapman Hall/CRC Texts in Statistical Science)
Fundamentals of Causal Inference: With R (Chapman & Hall/CRC Texts in Statistical Science)
by Babette A. Brumback

4.2 out of 5

Language : English
File size : 11937 KB
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The book was found!
Fundamentals of Causal Inference: With R (Chapman Hall/CRC Texts in Statistical Science)
Fundamentals of Causal Inference: With R (Chapman & Hall/CRC Texts in Statistical Science)
by Babette A. Brumback

4.2 out of 5

Language : English
File size : 11937 KB
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