R Dataset / Package MASS / npk

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-mass-npk.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-94871.csv 518 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 npk data set which pertains to Classical N, P, K Factorial Experiment. The npk data set is found in the MASS R package. You can load the npk data set in R by issuing the following command at the console data("npk"). This will load the data into a variable called npk. If R says the npk 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 npk R data set. The size of this file is about 518 bytes.


Classical N, P, K Factorial Experiment

Description

A classical N, P, K (nitrogen, phosphate, potassium) factorial experiment on the growth of peas conducted on 6 blocks. Each half of a fractional factorial design confounding the NPK interaction was used on 3 of the plots.

Usage

npk

Format

The npk data frame has 24 rows and 5 columns:

block

which block (label 1 to 6).

N

indicator (0/1) for the application of nitrogen.

P

indicator (0/1) for the application of phosphate.

K

indicator (0/1) for the application of potassium.

yield

Yield of peas, in pounds/plot (the plots were (1/70) acre).

Note

This dataset is also contained in R 3.0.2 and later.

Source

Imperial College, London, M.Sc. exercise sheet.

References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

Examples

options(contrasts = c("contr.sum", "contr.poly"))
npk.aov <- aov(yield ~ block + N*P*K, npk)
npk.aov
summary(npk.aov)
alias(npk.aov)
coef(npk.aov)
options(contrasts = c("contr.treatment", "contr.poly"))
npk.aov1 <- aov(yield ~ block + N + K, data = npk)
summary.lm(npk.aov1)
se.contrast(npk.aov1, list(N=="0", N=="1"), data = npk)
model.tables(npk.aov1, type = "means", se = TRUE)

--

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