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A handbook of statistical analyses using R

By: Hothorn, Torsten.
Contributor(s): Everitt, Brian.
Material type: materialTypeLabelBookPublisher: Boca Raton CRC Press 2014Edition: 3rd ed.Description: xxix, 421 p.ISBN: 9781482204582.Subject(s): Mathematical statistics - Data processing - Handbooks, manuals, etc | R - Computer program language - Handbooks, manuals, etc | Mathematical statistics - Data processingDDC classification: 519.502855133 Summary: Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition • Three new chapters on quantile regression, missing values, and Bayesian inference • Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables • Additional exercises • More detailed explanations of R code • New section in each chapter summarizing the results of the analyses • Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results. (https://www.crcpress.com/A-Handbook-of-Statistical-Analyses-using-R-Third-Edition/Hothorn-Everitt/9781482204582)
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Table of Contents:

1. An Introduction to R

2. Data Analysis Using Graphical Displays

3. Simple Inference

4. Conditional Inference

5. Analysis of Variance

6. Simple and Multiple Linear Regression

7. Logistic Regression and Generalized Linear Models

8. Density Estimation

9. Recursive Partitioning

10. Scatterplot Smoothers and Additive Models

11. Survival Analysis

12. Quantile Regression

13. Analysing Longitudinal Data I

14. Analysing Longitudinal Data II

15. Simultaneous Inference and Multiple Comparisons

16. Missing Values

17. Meta-Analysis

18. Bayesian Inference

19. Principal Component Analysis

20. Multidimensional Scaling

21. Cluster Analysis

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.

New to the Third Edition

• Three new chapters on quantile regression, missing values, and Bayesian inference
• Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables
• Additional exercises
• More detailed explanations of R code
• New section in each chapter summarizing the results of the analyses
• Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses

Whether you’re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.


(https://www.crcpress.com/A-Handbook-of-Statistical-Analyses-using-R-Third-Edition/Hothorn-Everitt/9781482204582)

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