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Library,Documentation and Information Science Division

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borderland which separates the known from the unknown”

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Statistics : an introduction using R / Michael J. Crawley.

By: Material type: TextTextPublication details: Chichester : John Wiley, c2015.Edition: 2nd edDescription: xiii, 339 p. : illustrations ; 25 cmISBN:
  • 9781118941096 (pbk.)
Subject(s): DDC classification:
  • 000SA.055 23 C911
Contents:
1. Fundamentals -- 2. Dataframes -- 3. Central tendency -- 4. Variance -- 5. Single samples -- 6. Two samples -- 7. Regression -- 8. Analysis of variance -- 9. Analysis of covariance -- 10. Multiple regression -- 11. Contrasts -- 12. Other response variables -- 13. Count data -- 14. Proportion data -- 15. Binary response variable -- 16. Death and failure data -- Appendix: Essentials of the R language -- References -- Further reading -- Index.
Summary: The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t––tests and chi––squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.055 C911 (Browse shelf(Opens below)) Available 136625
Books ISI Library, Kolkata 000SA.055 C911 (Browse shelf(Opens below)) Available 136624
Total holds: 0

Includes bibliographical references and index.

1. Fundamentals --
2. Dataframes --
3. Central tendency --
4. Variance --
5. Single samples --
6. Two samples --
7. Regression --
8. Analysis of variance --
9. Analysis of covariance --
10. Multiple regression --
11. Contrasts --
12. Other response variables --
13. Count data --
14. Proportion data --
15. Binary response variable --
16. Death and failure data --
Appendix: Essentials of the R language --
References --
Further reading --
Index.

The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t––tests and chi––squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.

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