R Dataset / Package MASS / Insurance

How To Create a Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Cumulative Frequency Histogram

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-mass-insurance.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-60526.csv 1.6 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the Insurance data set which pertains to Numbers of Car Insurance claims. The Insurance data set is found in the MASS R package. You can load the Insurance data set in R by issuing the following command at the console data("Insurance"). This will load the data into a variable called Insurance. If R says the Insurance data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Insurance R data set. The size of this file is about 1,643 bytes.

Documentation

Numbers of Car Insurance claims

Description

The data given in data frame Insurance consist of the numbers of policyholders of an insurance company who were exposed to risk, and the numbers of car insurance claims made by those policyholders in the third quarter of 1973.

Usage

Insurance

Format

This data frame contains the following columns:

District

factor: district of residence of policyholder (1 to 4): 4 is major cities.

Group

an ordered factor: group of car with levels <1 litre, 1–1.5 litre, 1.5–2 litre, >2 litre.

Age

an ordered factor: the age of the insured in 4 groups labelled <25, 25–29, 30–35, >35.

Holders

numbers of policyholders.

Claims

numbers of claims

Source

L. A. Baxter, S. M. Coutts and G. A. F. Ross (1980) Applications of linear models in motor insurance. Proceedings of the 21st International Congress of Actuaries, Zurich pp. 11–29.

M. Aitkin, D. Anderson, B. Francis and J. Hinde (1989) Statistical Modelling in GLIM. Oxford University Press.

References

Venables, W. N. and Ripley, B. D. (1999) Modern Applied Statistics with S-PLUS. Third Edition. Springer.

Examples

## main-effects fit as Poisson GLM with offset
glm(Claims ~ District + Group + Age + offset(log(Holders)),
    data = Insurance, family = poisson)# same via loglm
loglm(Claims ~ District + Group + Age + offset(log(Holders)),
      data = Insurance)
--

Dataset imported from https://www.r-project.org.

R Output Date
Picostat Output - Boxplot Apr 24, 2019
Picostat Output - Boxplot Apr 24, 2019
Picostat Output - Boxplot Apr 24, 2019
Picostat Output - Boxplot Apr 24, 2019
Picostat Output - Boxplot Apr 24, 2019