R Dataset / Package DAAG / rice

On this R-data statistics page, you will find information about the rice data set which pertains to Genetically Modified and Wild Type Rice Data. The rice data set is found in the DAAG R package. You can load the rice data set in R by issuing the following command at the console data("rice"). This will load the data into a variable called rice. If R says the rice 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 with the library() command. 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 rice R data set. The size of this file is about 2,680 bytes.

Genetically Modified and Wild Type Rice Data

Description

The rice data frame has 72 rows and 7 columns. The data are from an experiment that compared wild type (wt) and genetically modified rice plants (ANU843), each with three different chemical treatments (F10, NH4Cl, and NH4NO3).

Usage

rice

Format

This data frame contains the following columns:

PlantNo: a numeric vector
Block: a numeric vector
RootDryMass: a numeric vector
ShootDryMass: a numeric vector
trt: a factor with levels F10, NH4Cl, NH4NO3, F10 +ANU843, NH4Cl +ANU843, NH4NO3 +ANU843
fert: a factor with levels F10 NH4Cl NH4NO3
variety: a factor with levels wt ANU843

Source

Perrine, F.M., Prayitno, J., Weinman, J.J., Dazzo, F.B. and Rolfe, B. 2001. Rhizobium plasmids are involved in the inhibition or stimulation of rice growth and development. Australian Journal of Plant Physiology 28: 923-927.

Examples

print("One and Two-Way Comparisons - Example 4.5")
attach(rice)
oldpar <- par(las = 2)
stripchart(ShootDryMass ~ trt, pch=1, cex=1, xlab="Level of factor 1")
detach(rice)
pause()rice.aov <- aov(ShootDryMass ~ trt, data=rice); anova(rice.aov)
anova(rice.aov)
pause()summary.lm(rice.aov)$coef
pause()rice$trt <- relevel(rice$trt, ref="NH4Cl")
# Set NH4Cl as the baselinefac1 <- factor(sapply(strsplit(as.character(rice$trt)," \\+"), function(x)x[1]))
anu843 <- sapply(strsplit(as.character(rice$trt), "\\+"), 
function(x)c("wt","ANU843")[length(x)])
anu843 <- factor(anu843, levels=c("wt", "ANU843"))
attach(rice)
interaction.plot(fac1, anu843, ShootDryMass)
detach(rice)
par(oldpar)

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

Attachments: csv, json

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