R Dataset / Package datasets / chickwts

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<iframe src="https://embed.picostat.com/r-dataset-package-datasets-chickwts.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-57787.csv 1.03 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 chickwts data set which pertains to Chicken Weights by Feed Type. The chickwts data set is found in the datasets R package. You can load the chickwts data set in R by issuing the following command at the console data("chickwts"). This will load the data into a variable called chickwts. If R says the chickwts data set is not found, you can try installing the package by issuing this command install.packages("datasets") 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 chickwts R data set. The size of this file is about 1,053 bytes.

Documentation

Chicken Weights by Feed Type

Description

An experiment was conducted to measure and compare the effectiveness of various feed supplements on the growth rate of chickens.

Usage

chickwts

Format

A data frame with 71 observations on the following 2 variables.

weight

a numeric variable giving the chick weight.

feed

a factor giving the feed type.

Details

Newly hatched chicks were randomly allocated into six groups, and each group was given a different feed supplement. Their weights in grams after six weeks are given along with feed types.

Source

Anonymous (1948) Biometrika, 35, 214.

References

McNeil, D. R. (1977) Interactive Data Analysis. New York: Wiley.

Examples

require(stats); require(graphics)
boxplot(weight ~ feed, data = chickwts, col = "lightgray",
    varwidth = TRUE, notch = TRUE, main = "chickwt data",
    ylab = "Weight at six weeks (gm)")
anova(fm1 <- lm(weight ~ feed, data = chickwts))
opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0),
            mar = c(4.1, 4.1, 2.1, 1.1))
plot(fm1)
par(opar)
--

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

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