Modern Data Science with R

ISBN-13: 9780367191498 / Angielski / Twarda / 2021 / 632 str.

Benjamin S. Baumer; Daniel T. Kaplan; Nicholas J. Horton

Opis

This textbook is designed for an undergraduate course in data science that emphasizes topics in both statistics and computer science.

Spis treści

I Part I: Introduction to Data Science. 1. Prologue: Why data science? 2. Data visualization. 3. A grammar for graphics. 4. Data wrangling on one table. 5. Data wrangling on multiple tables. 6. Tidy data. 7. Iteration. 8. Data science ethics. II. Part II: Statistics and Modeling. 9. Statistical foundations. 10. Predictive modeling. 11. Supervised learning. 12. Unsupervised learning. 13. Simulation. III Part III: Topics in Data Science. 14. Dynamic and customized data graphics. 15. Database querying using SQL. 16. Database administration. 17. Working with spatial data. 18.Geospatial computations. 19. Text as data. 20. Network science. IV Part IV: Appendices.