Modern Data Science with R
eBook - ePub

Modern Data Science with R

  1. 556 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Modern Data Science with R

About this book

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling statistical questions.

Contemporary data science requires a tight integration of knowledge from statistics, computer science, mathematics, and a domain of application. This book will help readers with some background in statistics and modest prior experience with coding develop and practice the appropriate skills to tackle complex data science projects. The book features a number of exercises and has a flexible organization conducive to teaching a variety of semester courses.

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Yes, you can access Modern Data Science with R by Benjamin S. Baumer,Daniel T. Kaplan,Nicholas J. Horton in PDF and/or ePUB format, as well as other popular books in Mathematics & Statistics for Business & Economics. We have over one million books available in our catalogue for you to explore.

Indices

Separate indices are provided for subject (concept or task) and R command. References to the examples are denoted in italics.

Subject index

@ operator, 190
140 character limit, 370
1960s, 367
“A Boy Named Sue”, 101
A/B testing, 5, 162
Aadam, 102
Aaron, Hank, 82
access
databases, 492
elements, 427
variables, 449
accidental patterns, 149
accountability, 131
ACM, 143
actors, 382, 386, 387
actuarial tables, 49
add circles, 349
add rownames, 181
additional factor, 11
additional factors, 161
adjacency matrix, 395, 396
administration, database, 301
Adobe Illustrator, 254
Advanced R, 104, 439
adversarial system, 140
advertisers, 390
aesthetic, 33
fill, 34
graphical, 34, 387
multiple, 34
Africa, 324
afternoon, 160
age, 196
aggregating, 70, 181, 275
airline delays, see flight delays
airline route maps, 345
airport, 150, 346
codes, 282
Reagan National, 285, 308
Akten, Memo, 28
Alaska, 287, 350
Albers projection, 324
Albert
Jim, xxvi, 88
Réka, 380
Alderson, Sandy, 77
algorithmic thinking, 3, 443, 453
alias
table, 283
alive, 49
Allaire, J.J., xxvi
Alon, Noga, 382
alpha level, 166
Altavista, 390
alter database, 303
ALTER statement, see SQL
Amazon, 261, 401
Web Services, 412
ambient temperature, 24
American Airlin...

Table of contents

  1. Cover Page
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. List of Tables
  7. List of Figures
  8. Preface
  9. I Introduction to Data Science
  10. II Statistics and Modeling
  11. III Topics in Data Science
  12. IV Appendices
  13. Bibliography
  14. Indices