Apress, 2025. — 222 p. — ISBN: 9798868805790. This book is not a comprehensive guide; if that's what you're seeking, you may want to look elsewhere. Instead, it serves as a map, outlining the necessary tools and topics for your research journey. The goal is to build your intuition and provide pointers for where to find more detailed information. The chapters are deliberately...
San Francisco: No Starch Press, 2024. — 251 p. — ISBN: 1718503326. Learn how to use R for everything from workload automation and creating online reports, to interpreting data, map making, and more. The R programming language is a remarkably powerful tool for data analysis and visualization, but its steep learning curve can be intimidating for some. If you just want to automate...
SAGE Publications, 2020. — 537 p. — ISBN: 9781544324579. Neil J. Salkind’s best-selling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it was first published in 2000. Now the best-selling SPSS and Excel versions are joined by a text for use with the R software, Statistics for People Who...
John Wiley & Sons, Inc., 2021. — 356 p. — ISBN: 978-93-90421-47-3. With the widespread and exponential growth of data, people with data science backgrounds are in great demand. Data analytics, a subdomain of data science, is meant to turn data into insight and actionable knowledge. Data analytics mainly deals with exploring, visualizing, transforming, and modeling data for...
3rd ed. — John Wiley & Sons, 2022. — 576 p. — ISBN: 1119874033. This thoroughly updated third edition combines the latest software applications with the benefits of modern resampling techniques. Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The third edition of Mathematical...
3rd Edition. — Wiley, 2022. — 576 p. — eBook ISBN: 978-1-119-87404-1. This thoroughly updated third edition combines the latest software applications with the benefits of modern resampling techniques. Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. The third edition of...
2nd Edition. — SAGE Publications Ltd, 2023. — 448 p. — ISBN: 978-1529753530. Statistics is made simple with this award-winning guide to using R and applied statistical methods. With a clear step-by-step approach explained using real-world examples, learn the practical skills you need to use statistical methods in your research from an expert with over 30 years of teaching...
2nd Edition. — CRC Press, 2024. — 466 p. — (Chapman & Hall/CRC Texts in Statistical Science). — ISBN: 978-1-032-75197-9. Praise for the first edition: “This book would be especially good for the shelf of anyone who already knows nonparametrics, but wants a reference for how to apply those techniques in R.”. The American Statistician. This thoroughly updated and expanded second...
2nd Edition. — Chapman & Hall, 2024.. — 706 p. — eBook ISBN: 9781003093091. Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio...
Birmingham: Packt Publishing, 2024. - 375 p. - ISBN: 1837639027. Master the fundamentals of advanced techniques of causal inference through a practical, hands-on approach with extensive R code examples and real-world applications. Key Features Explore causal analysis with hands-on R tutorials and real-world examples. Grasp complex statistical methods by taking a detailed,...
James Gareth, Witten Daniela, Hastie Trevor, Tibshirani Robert. Springer Science+Business Media New York, 2013. - 436 p. This is a comprehensive textbook on statistical learning. The book provides an accessible introduction to the field, covering key topics and techniques in statistical learning, with a focus on applications in R. The book focuses on statistical learning, a...
2nd Edition. — Routledge, 2025. — 321 p. — (Quantitative Methodology Series). — ISBN: 978-1-032-61940-8. This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (“latent”) variables. Although the focus is on simple R code, the book provides updated guidance...
Singapore: World Scientific Publishing Company, 2024. - 302 p. - ISBN: 9811297479. Cluster analysis is a fundamental data analysis task that aims to group similar data points, revealing the inherent structure and patterns within complex datasets. This book serves as a comprehensive and accessible guide, taking readers on a captivating journey through the foundational principles...
Independently published, 2024. — 283 p. Welcome to "R Programming for Data Science", a comprehensive guide that will take you on a journey from the basics of R programming to advanced techniques for working with data in the context of Data Science. As someone interested in Data Science, you're likely aware of the importance of having a strong foundation in programming and data...
Norwich (U.K.): Vor Press, 2023. — 248 p. — (Statistics without Mathematics). — ISBN: 978-1915500044. Statistics is a seemingly very mysterious yet necessary subject at the graduate level. Many graduate students are required to use statistics to carry out their research, be their study in science, medicine, engineering, business, or social sciences. Most universities provide...
Norwich (U.K.): Vor Press, 2023. - 248 p. - ISBN: 1915500044. Statistics is a seemingly very mysterious yet necessary subject at the graduate-level. Many graduate students are required to use statistics to carry out their research, be their study in science, medicine, engineering, business, or social sciences. Most universities provide basic courses in statistics for students...
2nd Edition. — CRC Press, 2025. — 688 p. — ISBN: 9780367553234. Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and...
Independently published, 2024. — 138 p. — (Computer Programming). — ASIN: B0DF3VL19J. Unlock Your Data Science Potential with R Programming! Dive into “R Programming: Mastering Data Science and Statistical Computing”, the ultimate guide to one of the most powerful tools in the world of Data Science. Whether you're a complete beginner or an experienced professional looking to...