R data analysis without programming: explanation and interpretation /
Edition statement:2nd ed. Published by : Routledge, (New York, NY : ) Physical details: xx, 357 pages : illus. ; 28 cm. ISBN:9781032244037. Year: 2023| Item type | Current location | Collection | Call number | Status | Date due | Barcode |
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ASCOT Library - Zabali Campus Reference | Reference | Ref 005.133 G31r 2023. (Browse shelf) | Available | Ref0051304673 |
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| Ref 005.133 F24j 2010. Java Programming / | Ref 005.133 F24j 2016. Java Programming / | Ref 005.133 F24j 2023. Java programming / | Ref 005.133 G31r 2023. R data analysis without programming: explanation and interpretation / | Ref 005.43 Ec57l 2020 Linux+ and LPIC-1 guide to Linux certification / | Ref 005.52 C15m 2023. Microsoft 365, Office 2021 : advanced / | Ref 005.71 M91m 2023 Multimedia big data computing for IoT applications: concepts, paradigms and solutions / |
1. R for Data Analysis. --
2. Read and Write Data. --
3. Manage Data. --
4. Categorical Variables. --
5. Continuous Variables. --
6. Statistics. --
7. Compare Two Samples. --
8. Compare Multiple Samples. --
9. Factorial Designs. --
10. Correlation. --
11. Regression Analysis. --
12. Multiple Regression. --
13. Categorical Regression Variables. --
14. Causality. --
15. Item and Factor Analysis. --
16. References. --
17. Index.
"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"-- Provided by publisher
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