A Handbook of Statistical Analyses Using R (3rd Edition)

Vignettes

- An Introduction to R
- Chapter Analysis of Variance
- Chapter Analyzing Longitudinal Data I
- Chapter Analyzing Longitudinal Data II
- Chapter Bayesian Inference
- Chapter Cluster Analysis
- Chapter Conditional Inference
- Chapter Data Analysis using Graphical Displays
- Chapter Density Estimation
- Chapter Generalized Additive Models
- Chapter Logistic Regression and Generalized Linear Models
- Chapter Meta-Analysis
- Chapter Missing Values
- Chapter Multidimensional Scaling
- Chapter Principal Component Analysis
- Chapter Quantile Regression
- Chapter Recursive Partitioning
- Chapter Simple Inference
- Chapter Simultaneous Inference and Multiple Comparisons
- Chapter Survival Analysis
- Errata
- Multiple Linear Regression

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Description Usage Format Details Source Examples

Percentage incidence of the 13 characteristics of water voles in 14 areas.

1 | ```
data("watervoles")
``` |

A dissimilarity matrix for the following 14 variables, i.e,
areas:
`Surrey`

,
`Shropshire`

,
`Yorkshire`

,
`Perthshire`

,
`Aberdeen`

,
`Elean Gamhna`

,
`Alps`

,
`Yugoslavia`

,
`Germany`

,
`Norway`

,
`Pyrenees I`

,
`Pyrenees II`

,
`North Spain`

, and
`South Spain`

.

Corbet et al. (1970) report a study of water voles (genus Arvicola) in which the aim was to compare British populations of these animals with those in Europe, to investigate whether more than one species might be present in Britain. The original data consisted of observations of the presence or absence of 13 characteristics in about 300 water vole skulls arising from six British populations and eight populations from the rest of Europe. The data are the percentage incidence of the 13 characteristics in each of the 14 samples of water vole skulls.

G. B. Corbet, J. Cummins, S. R. Hedges, W. J. Krzanowski (1970),
The taxonomic structure of British water voles, genus *Arvicola*.
*Journal of Zoology*, **61**, 301–316.

1 2 | ```
data("watervoles", package = "HSAUR3")
watervoles
``` |

HSAUR3 documentation built on Aug. 19, 2017, 1:02 a.m.

An Introduction to R
Chapter Analysis of Variance
Chapter Analyzing Longitudinal Data I
Chapter Analyzing Longitudinal Data II
Chapter Bayesian Inference
Chapter Cluster Analysis
Chapter Conditional Inference
Chapter Data Analysis using Graphical Displays
Chapter Density Estimation
Chapter Generalized Additive Models
Chapter Logistic Regression and Generalized Linear Models
Chapter Meta-Analysis
Chapter Missing Values
Chapter Multidimensional Scaling
Chapter Principal Component Analysis
Chapter Quantile Regression
Chapter Recursive Partitioning
Chapter Simple Inference
Chapter Simultaneous Inference and Multiple Comparisons
Chapter Survival Analysis
Errata
Multiple Linear Regression

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