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Modern Data Science With R (Record no. 48029)

MARC details
000 -LEADER
fixed length control field 02173cam a2200301 i 4500
003 - CONTROL NUMBER IDENTIFIER
control field RNL
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260330044826.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 201130s2021 flu ob 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781032941677
040 ## - CATALOGING SOURCE
Original cataloging agency RCL
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312 B341M
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Baumer, Benjamin,
245 10 - TITLE STATEMENT
Title Modern Data Science With R
Statement of responsibility, etc / Benjamin S. Baumer, Daniel T. Kaplan, and Nicholas J. Horton.
250 ## - EDITION STATEMENT
Edition statement 2nd.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication Oxford:
Name of publisher CRC Press,
Year of publication 2025.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xvii, 631p. ; 24cm.
Other physical details illustration;
490 0# - SERIES STATEMENT
Series statement Chapman and Hall/CRC Press texts in statistical science
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and indexes.
520 ## - SUMMARY, ETC.
Summary, etc "Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. 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 questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice. From a review of the first edition: "Modern Data Science with R ... is rich with examples and is guided by a strong narrative voice. What's more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician)"--
546 ## - LANGUAGE NOTE
Language note English
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Big data.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Mathematical statistics
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term R (Computer program language)
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Kaplan, Daniel,
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Horton, Nicholas J.,
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Full call number Accession Number Cost, replacement price Lost status Damaged status Price effective from Koha item type Not for loan Collection code Withdrawn status Home library Current library Shelving location Date acquired Cost, normal purchase price
006.312 B341M 65868 3495.00     03/30/2026 Books   Statistics Department Books   RCL RCL General Stacks 03/06/2026 3495.00

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