/R-Tutorial-for-Data-analysis

Tutorial for Data Analysis using R

R-Tutorial-for-Data-analysis #Tutorial for Data Analysis using R

The aim of this tutorial is to help you get started using the R environment for scientific data analysis.

The workflow for data analysis: Import; Check; Describe; Transform; Analyse the Data and Store important results such as graphics or tables as files.

You may find a list of available data sets by typing data() at the console.

We use the data set PlantGrowth. To get basic info

?PlantGrowth PlantGrowth snip

Summary information via summary (PlantGrowth)

summary(PlantGrowth)

To get summary information for each level of the group variable,

for each treatment) use

by(PlantGrowth, PlantGrowth$group, summary)

to get a boxplot of weight separately by group, use the comman boxplot

?boxplot boxplot(weight~group, data = PlantGrowth)

The plot still lacks some labels, which we add (together with some color for the boxes)

boxplot(weight ~ group, data=PlantGrowth, main="Plant Growth data", ylab="Dried plant weight", col="cyan")

perform an analysis of variance use lm(), Our model is pg.lm:

pg.lm <- lm(weight ~ group, data=PlantGrowth) pg.lm

To get a bit more information, use summary(pg.lm)

summary(pg.lm)

To test the signifcance of the group difference,

anova(pg.lm)

using the plot command #demonstrate methods of plot() function

plot(PlantGrowth) plot(pg.lm)

#clean up rm(pg.lm)