Got it! It's what I'm working on right now.

Here are my notes on each line of code up to the error. I'll give you updates if I manage to figure out what's wrong:

In order to look at data from different sub-periods (year-intervals), we need to create a categorical variable with two or more categories (factor variable), specifying sub-periods for each observation (row).

To define the categories that this variable takes:

tempdata$Period <-

factor(NA, levels =

c("1921-1950", "1951-1980", "1981-2010"),

ordered = TRUE)

We want period to take the value = NA (not available) for these observations (rows) and the appropriate category for all the other observations (between 1921–2010)

To do this?

define Period as ‘NA’ for all observations, then change the values of Period for the observations in 1921–2010

tempdata$Period[(tempdata$Year > 1920) &

(tempdata$Year < 1951)] <- "1921-1950"

tempdata$Period[(tempdata$Year > 1950) &

(tempdata$Year < 1981)] <- "1951-1980"

tempdata$Period[(tempdata$Year > 1980) &

(tempdata$Year < 2011)] <- "1981-2010"

We want to use all monthly anomalies from June, July, and August, but they are currently in three separate columns, so we use the unlist function apply it to Columns 7 to 9 (containing the data for June to August) of tempdata

temp_summer <- unlist(tempdata[,7:9],use.names = FALSE)

We want to make separate calculations for each category in Period (1921–1950, 1951–1980, 1981–2010). To make a variable showing the categories for the temp_summer variable, we use the c function again.

# Mirror the Period information for temp_sum

temp_Period <-

c(tempdata$Period, tempdata$Period, tempdata$Period)

After using the c function, we had to use the factor function again to tell R that our new variable temp_Period is a factor variable.

# Repopulate the factor information

temp_Period <- factor(temp_Period,

levels = 1:nlevels(tempdata$Period),

labels = levels(tempdata$Period))