iris3

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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Visual

How To Compute the Mean

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Numerical
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How To Create a Plot

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Visual
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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

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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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Ratio

Submitted by pmagunia on December 18, 2021 - 4:28 PM

Regression

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

Stem and Leaf Plots

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

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Submitted by pmagunia on February 26, 2017 - 11:28 AM
<iframe src="https://embed.picostat.com/iris3.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-17099.csv 2.44 KB
Documentation

Edgar Anderson's Iris Data

This famous (Fisher's or Anderson's) iris data set gives the measurements in centimeters of the variables sepal length and width and petal length and width, respectively, for 50 flowers from each of 3 species of iris. The species are Iris setosa, versicolor, and virginica.

Usage

iris
iris3

Format

iris is a data frame with 150 cases (rows) and 5 variables (columns) named Sepal.Length, Sepal.Width, Petal.Length, Petal.Width, and Species.

iris3 gives the same data arranged as a 3-dimensional array of size 50 by 4 by 3, as represented by S-PLUS. The first dimension gives the case number within the species subsample, the second the measurements with names Sepal L., Sepal W., Petal L., and Petal W., and the third the species.

Source

Fisher, R. A. (1936) The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, Part II, 179–188.

The data were collected by Anderson, Edgar (1935). The irises of the Gaspe Peninsula, Bulletin of the American Iris Society, 59, 2–5.

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole. (has iris3 as iris.)

See Also

matplot some examples of which use iris.

Examples

dni3 <- dimnames(iris3)
ii <- data.frame(matrix(aperm(iris3, c(1,3,2)), ncol = 4,
                        dimnames = list(NULL, sub(" L.",".Length",
                                        sub(" W.",".Width", dni3[[2]])))),
    Species = gl(3, 50, labels = sub("S", "s", sub("V", "v", dni3[[3]]))))
all.equal(ii, iris) # TRUE
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    • Dotplot
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    • Pie Chart
    • Regression - Perform a simple linear regression and compute the p-value and regression line. Also plots the data with the regression line.
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    • Visual Summaries - plots the following:
      1. Frequency Histogram
      2. Relative Frequency Histogram
      3. Cumulative Frequency Histogram
      4. Boxplot (Box-and-whisker plot)
      5. Dotplot
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    • How To Compute the Mean - This application will show you how to compute the mean from a column vector
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