R Dataset / Package robustbase / wood

How To Create a Barplot

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Visual
Instructional

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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Numerical
Instructional

How To Create a Plot

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How to Compute the Median

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Numerical

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

Submitted by pmagunia on April 22, 2018 - 3:10 PM
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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

Submitted by pmagunia on April 22, 2018 - 3:12 PM
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Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM
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Submitted by pmagunia on March 9, 2018 - 1:06 PM
<iframe src="https://embed.picostat.com/r-dataset-package-robustbase-wood.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-48793.csv 761 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 wood data set which pertains to Modified Data on Wood Specific Gravity. The wood data set is found in the robustbase R package. You can load the wood data set in R by issuing the following command at the console data("wood"). This will load the data into a variable called wood. If R says the wood data set is not found, you can try installing the package by issuing this command install.packages("robustbase") 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 wood R data set. The size of this file is about 761 bytes.


Modified Data on Wood Specific Gravity

Description

The original data are from Draper and Smith (1966) and were used to determine the influence of anatomical factors on wood specific gravity, with five explanatory variables and an intercept. These data were contaminated by replacing a few observations with outliers.

Usage

data(wood)

Format

A data frame with 20 observations on the following 6 variables.

x1, x2, x3, x4, x5

explanatory “anatomical” wood variables.

y

wood specific gravity, the target variable.

Source

Draper and Smith (1966, p.227)

Peter J. Rousseeuw and Annick M. Leroy (1987) Robust Regression and Outlier Detection Wiley, p.243, table 8.

Examples

data(wood)
plot(wood)
summary( lm.wood <-        lm(y ~ ., data = wood))
summary(rlm.wood <- MASS::rlm(y ~ ., data = wood))
summary(lts.wood <-    ltsReg(y ~ ., data = wood))wood.x <- as.matrix(wood)[,1:5]
c_wood <- covMcd(wood.x)
c_wood

--

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