R Data Analysis Without Programming - Info and Reading Options
Explanation and Interpretation
By David W. Gerbing
"R Data Analysis Without Programming" was published by Routledge, Chapman & Hall, Incorporated in 2022 - New York, NY, it has 358 pages and the language of the book is English.
“R Data Analysis Without Programming” Metadata:
- Title: ➤ R Data Analysis Without Programming
- Author: David W. Gerbing
- Language: English
- Number of Pages: 358
- Publisher: ➤ Routledge, Chapman & Hall, Incorporated
- Publish Date: 2022
- Publish Location: New York, NY
“R Data Analysis Without Programming” Subjects and Themes:
- Subjects: ➤ Mathematical statistics - Programming languages (electronic computers) - R (Computer program language) - Data processing - PSYCHOLOGY / Statistics - BUSINESS & ECONOMICS / Statistics - EDUCATION / Statistics - PSYCHOLOGY - Statistics - BUSINESS & ECONOMICS - EDUCATION - MATHEMATICS - Applied - Probability & Statistics - General - Datenanalyse - Datenverarbeitung - R. - Statistik
Edition Specifications:
- Pagination: 378
Edition Identifiers:
- The Open Library ID: OL39722826M - OL17534106W
- ISBN-13: 9781032244020 - 9781032244037
- All ISBNs: 9781032244020 - 9781032244037
AI-generated Review of “R Data Analysis Without Programming”:
"R Data Analysis Without Programming" Description:
Open Data:
"The new edition of this innovative book, R Data Analysis Without Programming, prepares the readers to quickly analyse data and interpret statistical results using R. Professor Gerbing has developed lessR, which is a ground-breaking method in alleviating the challenges of R programming. The lessR extends R, removing the need for programming. This edition expands upon the first edition's introduction to R through lessR which enables the readers to learn how to organize data for analysis, read the data into R, and generate output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables with simple function calls. The text reviews and explains basic statistical procedures with the lessR enhancements added to the standard R environment. Using lessR, data analysis with R becomes immediately accessible to the novice user and easier to use for the experienced user"--
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