R Dataset / Package DAAG / allbacks

How To Create a Barplot

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How To Create a Stacked 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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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Regression

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Stem and Leaf Plots

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Visual Summaries

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Submitted by pmagunia on March 9, 2018 - 1:06 PM
<iframe src="https://embed.picostat.com/r-dataset-package-daag-allbacks.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-92676.csv 280 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the allbacks data set which pertains to Measurements on a Selection of Books. The allbacks data set is found in the DAAG R package. You can load the allbacks data set in R by issuing the following command at the console data("allbacks"). This will load the data into a variable called allbacks. If R says the allbacks data set is not found, you can try installing the package by issuing this command install.packages("DAAG") 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 allbacks R data set. The size of this file is about 280 bytes.


Measurements on a Selection of Books

Description

The allbacks data frame gives measurements on the volume and weight of 15 books, some of which are softback (pb) and some of which are hardback (hb). Area of the hardback covers is also included.

Usage

allbacks

Format

This data frame contains the following columns:

volume

book volumes in cubic centimeters

area

hard board cover areas in square centimeters

weight

book weights in grams

cover

a factor with levels hb hardback, pb paperback

Source

The bookshelf of J. H. Maindonald.

Examples

print("Multiple Regression - Example 6.1")
attach(allbacks)
volume.split <- split(volume, cover)
weight.split <- split(weight, cover)
plot(weight.split$hb ~ volume.split$hb, pch=16, xlim=range(volume), ylim=range(weight),
     ylab="Weight (g)", xlab="Volume (cc)")
points(weight.split$pb ~ volume.split$pb, pch=16, col=2)
pause()allbacks.lm <- lm(weight ~ volume+area)
summary(allbacks.lm)
detach(allbacks)
pause()anova(allbacks.lm)
pause()model.matrix(allbacks.lm)
pause()print("Example 6.1.1")
allbacks.lm0 <- lm(weight ~ -1+volume+area, data=allbacks)
summary(allbacks.lm0)
pause()print("Example 6.1.2")
oldpar <- par(mfrow=c(2,2))
plot(allbacks.lm0)
par(oldpar)
allbacks.lm13 <- lm(weight ~ -1+volume+area, data=allbacks[-13,])
summary(allbacks.lm13)
pause()print("Example 6.1.3")
round(coef(allbacks.lm0),2)  # Baseline for changes
round(lm.influence(allbacks.lm0)$coef,2)

--

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