R Notebook

This is just an example comparative boxplot, don’t worry about the code (It’s just there for those who are interested!) - what we’re interested in is how boxplots can be useful to understand data.

First we pull the data from the google form in

aei_spring1 <- read.csv('https://docs.google.com/spreadsheets/d/1dZm2G6us40__A4tBr5SZj-LQEMSMv3h5fr5xxASltlU/export?gid=1383463932&format=csv')
aei_spring2 <- read.csv('https://docs.google.com/spreadsheets/d/1dZm2G6us40__A4tBr5SZj-LQEMSMv3h5fr5xxASltlU/export?gid=505023461&format=csv')

For example This is the raw Spring data (before it was cleaned)

aei_spring1[c(2,3,4,5,6)]

For example This is the cleaned up spring data (changing everything to cm)

aei_spring2[c(2,3,4,5,6)]

Boxplot for the raw (uncleaned) spring data - # what problems can you immediately see? # Do you think some tables decided on a consistent measurement? # Do the boxplots help you see which groups more people used cm vs mm (e.g. what’s the difference between table 6 and table 10?)

boxplot(What.length.is.your.left.ear..from.the.top.to.the.bottom.of.the.ear.. ~ What.is.your.table.number., data = aei_spring1)

aei_spring2$What.is.your.table.number. <- paste0(aei_spring2$What.is.your.table.number.,"_clean")
head(aei_spring2$What.is.your.table.number.)

[1] "10_clean" "4_clean"  "4_clean"  "6_clean"  "4_clean"  "5_clean" 

Boxplot for the raw and cleaned Spring data - makes it pretty obvious now?

aei_spring <- rbind(aei_spring1, aei_spring2)
boxplot(What.length.is.your.left.ear..from.the.top.to.the.bottom.of.the.ear.. ~ What.is.your.table.number., data = aei_spring, las=2)

Boxplot showing the cleaned Spring and summer data

aei_spr_sum <- rbind(aei_spring2, aei_summer)
boxplot(What.length.is.your.left.ear..from.the.top.to.the.bottom.of.the.ear.. ~ What.is.your.table.number., data = aei_spr_sum, las=2, par(mar = c(7,3,1,1)))

Boxplot showing the summer data - do you think it needs cleaning?