A Handbook of Statistical Analyses Using R (2nd Edition)

Vignettes

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

52

**CHFLS:**Chinese Health and Family Life Survey**Forbes2000:**The Forbes 2000 Ranking of the World's Biggest Companies...**gardenflowers:**Garden Flowers**pottery:**Romano-British Pottery Data**skulls:**Egyptian Skulls**toothpaste:**Toothpaste Data**USairpollution:**Air Pollution in US Cities**Browse all...**

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Description Usage Format Details Source Examples

Air pollution data of 41 US cities.

1 | ```
data("USairpollution")
``` |

A data frame with 41 observations on the following 7 variables.

`SO2`

SO2 content of air in micrograms per cubic metre.

`temp`

average annual temperature in Fahrenheit.

`manu`

number of manufacturing enterprises employing 20 or more workers.

`popul`

population size (1970 census); in thousands.

`wind`

average annual wind speed in miles per hour.

`precip`

average annual precipitation in inches.

`predays`

average number of days with precipitation per year.

The annual mean concentration of sulphur dioxide, in micrograms per cubic metre, is a measure of the air pollution of the city. The question of interest here is what aspects of climate and human ecology as measured by the other six variables in the data determine pollution?

R. R. Sokal and F. J. Rohlf (1981), *Biometry*,
W. H. Freeman, San Francisco (2nd edition).

1 | ```
data("USairpollution", package = "HSAUR2")
``` |

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

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