Statistical Inference via Data Science by Chester Ismay and Albert Y. Kim
Statistical Inference via Data Science - Table of Contents
PART I – GETTING STARTED WITH DATA IN R
- 1. Getting Started with Data in R and RStudio
PART II – DATA SCIENCE WITH TIDYVERSE
- 2. Data Visualization using ggplot2
- 3. Tidyverse Data Wrangling with dplyr
- 4. Data Importing and Tidy Data Principles
PART III – DATA MODELING WITH MODERNDIVE
- 5. Basic Linear Regression Modeling
- 6. Multiple Regression Analysis
PART IV – STATISTICAL INFERENCE WITH INFER
- 7. Sampling Distributions
- 8. Bootstrapping and Confidence Intervals
- 9. Hypothesis Testing and Permutations
- 10. Statistical Inference with R for Regression
PART V & APPENDICES – CONCLUSION & RESOURCES
- 11. R Programming and Data Science Storytelling
- Appendix A – Statistical Background
- Appendix B – Versions of R Packages Used
What You Will Learn in Statistical Inference via Data Science
Statistical Inference via Data Science by Chester Ismay and Albert Y. Kim is an essential practical manual written for university students, quantitative researchers, and data analysts. Serving as a premier r programming and data science textbook for beginners, this volume bridges real-world data collection with modern statistical inference tools.
Ismay and Kim’s code-driven exposition enables readers to learn statistical inference with r step-by-step. Topics transition seamlessly from data visualization and wrangling via the tidyverse to sampling distributions, confidence intervals, hypothesis testing, and linear regression, making this a complete moderndive statistical inference pdf study reference.
Ideal for introductory statistics courses, R programming bootcamps, and self-taught analysts, this open-access classic offers an outstanding free r data science textbook for students. Available as an accessible educational resource, it stands as an indispensable applied statistics study guide for self-learners mastering modern tidyverse workflows.
Book Details & Specifications
Title:
Statistical Inference via Data Science by Chester Ismay and Albert Y. Kim
Publisher:
University of Zagreb (FOI)
Year:
2025
Pages:
461
Type:
PDF
Language:
English
ISBN-10 #:
0367409828
ISBN-13 #:
978-0367409821
License:
CC BY-NC-SA 4.0
Amazon:
Amazon
About the Author: Chester Ismay and Albert Y. Kim
The author Chester Ismay and Albert Y. Kim
(Data Science Educator and Consultant) and Albert Y. Kim (Associate Professor of Statistical & Data Sciences at Smith College) are leading experts in statistics education and active contributors to the R and open-source communities.
Their open-access CRC Press textbook, Statistical Inference via Data Science PDF by Ismay and Kim (popularly known as ModernDive), is globally celebrated for transforming statistical pedagogy through computational R data tools.
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