R book / by Michael J.

By:

Crawley, Michael J

Material type: Text

TextLanguage: English Publication details: John Wiley & Sons, 2013. United Kingdom:Description: xxiv, 1051 pISBN:

9780470973929

Subject(s):

Mathematical statistics

DDC classification:

519.502855133 CRA-R

Contents:

1. Getting Started -- 2. Essentials of the R Language -- 3. Data Input -- 4. Dataframes -- 5. Graphics -- 6 Tables -- 7. Mathematics -- 8. Classical Tests -- 9. Statistical Modelling -- 10. Regression -- 11. Analysis of Variance -- 12. Analysis of Covariance -- 13. Generalized Linear Models -- 14. Count Data -- 15. Count Data in Tables -- 16. Proportion Data -- 17. Binary Response Variables -- 18. Generalized Additive Models -- 19. Mixed-Effects Models -- 20. Non-linear Regression -- 21. Meta-analysis -- 22. Bayesian statistics -- 23. Tree Models -- 24. Time Series Analysis -- 25. Multivariate Statistics -- 26. Spatial Statistics -- 27. Survival Analysis -- 28. Simulation Models -- 29. Changing the Look of Graphics.

Summary: "Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.

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Holdings
Item type	Current library	Collection	Call number	Status	Barcode
Text/Reserve Book	Library, SPAB G-1	Non Fiction	519.502855133 CRA-R (Browse shelf(Opens below))	Available	006104

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1. Getting Started --
2. Essentials of the R Language --
3. Data Input --
4. Dataframes --
5. Graphics --
6 Tables --
7. Mathematics --
8. Classical Tests --
9. Statistical Modelling --
10. Regression --
11. Analysis of Variance --
12. Analysis of Covariance --
13. Generalized Linear Models --
14. Count Data --
15. Count Data in Tables --
16. Proportion Data --
17. Binary Response Variables --
18. Generalized Additive Models --
19. Mixed-Effects Models --
20. Non-linear Regression --
21. Meta-analysis --
22. Bayesian statistics --
23. Tree Models --
24. Time Series Analysis --
25. Multivariate Statistics --
26. Spatial Statistics --
27. Survival Analysis --
28. Simulation Models --
29. Changing the Look of Graphics.

"Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.

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