Data Science Books Reviews

Here I will post some short reviews of the books I have read and own about data science. If you are reading this, some background: I am a researcher trained in dentistry and radiology, not mathematics. So I started reading and learning about statistics with all the knowledge gaps, but mostly with an opportunistic focus: now I have a problem, how should I solve it? So my comments on the books are mostly about how well they give me tools to solve my problems with data. For a (mostly) list of all my books, check here

WORK IN PROGRESS

Data Science in general

*Working with R (R Fundamentals Book 1 and 2) Stephanie Locke *R for Data Science: Import, Tidy, Transform, Visualize, and Model Data Hadley Wickham

Stats & Biostatistics

• A Student’s Guide to Bayesian Statistics Ben Lambert

• Statistics with Confidence: Confidence Intervals and Statistical Guidelines Douglas Altman

• Using Multivariate Statistics (4th Edition) Barbara G. Tabachnick(https://www.librarything.com/authorlink.php?book=132735618)

Data Visualization

*Data Visualization: A Practical Introduction Kieran Healy

Epidemiologic analysis

• Statistical Models in Epidemiology by David Clayton

Specific topics

• Practical R for Mass Communication and Journalism (Chapman & Hall/CRC The R Series) *How to Report Statistics in Medicine: Annotated Guidelines for Authors, Editors, and Reviewers Thomas A. Lang

• Applied Meta-Analysis with R (Chapman & Hall/CRC Biostatistics Series) Ding-Geng (Din) Chen 2013 meta-analysis, systematic review, rstats

• Meta-Analysis with R (Use R!) [Guido Schwarzer]

Specific for clinicians

• Oxford Handbook of Medical Statistics (Oxford Medical Handbooks) Janet Peacock

Sorting

• Exploratory Data Analysis (Quantitative Applications in the Social Sciences) Frederick Hartwig

• Statistical and Methodological Aspects of Oral Health Research (Statistics in Practice) Emmanuel Lesaffre

• Applied logistic regression (Wiley Series in probability and statistics) David W. Hosmer

• Statistical Inference via Data Science: A ModernDive into R and the Tidyverse Chester Ismay

• An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) Gareth James

• Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer Series in Statistics) Frank E. Harrell Jr.

• Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (Statistics for Biology and Health) Ewout W. Steyerberg

• A Handbook of Statistical Analyses using R, Third Edition Torsten Hothorn

• Biostatistics for Epidemiology and Public Health Using R Bertram K. C. Chan PhD

• OpenIntro Statistics, FULL COLOR Hardcover David M Diez

• Graphing Data with R: An Introduction John Jay Hilfiger

• Doing Bayesian Data Analysis: A Tutorial with R and BUGS John K. Kruschke

• Discovering Statistics Using R Andy Field

• Introductory statistics with R Peter

• Basic Statistics and Epidemiology: A Practical Guide, Fourth Edition Antony Stewart

• The Art of Statistics: How to Learn from Data David Spiegelhalter

• Biostats: Data Analysis for Dental Health Care Professionals Jane A. Weintraub

• Statistics: The Art and Science of Learning from Data (3rd Edition) Alan Agresti

• An Introduction to Categorical Data Analysis (Wiley Series in Probability and Statistics) Alan Agresti

• Statistics: An Introduction Using R Michael J. Crawley

• Practical Statistics for Data Scientists: 50 Essential Concepts Peter Bruce

• Statistics for Biologists Campbell

• Biostatistics for Oral Healthcare Jay Kim

• Statistics in Dentistry John Bulman